Triple
T16913842
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LKPR |
E410270
|
entity |
| Predicate | hasTerminal |
P182
|
FINISHED |
| Object |
Terminal 2
Terminal 2 is one of the passenger terminals at Václav Havel Airport Prague, primarily serving flights within the Schengen Area.
|
E413618
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Terminal 2 | Statement: [LKPR, hasTerminal, Terminal 2]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Terminal 2 Context triple: [LKPR, hasTerminal, Terminal 2]
-
A.
Terminal 2
Terminal 2 is a major passenger terminal at Ronald Reagan Washington National Airport serving numerous domestic airline operations and traveler amenities.
-
B.
Terminal 2
Terminal 2 is one of the passenger terminals at Chicago O'Hare International Airport, serving various domestic and regional flights with multiple concourses and airline operations.
-
C.
Terminal 2
Terminal 2 is a secondary passenger terminal at Kota Kinabalu International Airport in Sabah, Malaysia, serving regional and low-cost airline operations.
-
D.
Terminal 2
Terminal 2 is one of the main passenger terminals at Soekarno–Hatta International Airport in Jakarta, serving a large share of the airport’s domestic and international flights.
-
E.
Terminal 2
Terminal 2 is one of the passenger terminals serving Iași International Airport in Romania, handling check-in, departures, and arrivals for commercial flights.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Terminal 2 Triple: [LKPR, hasTerminal, Terminal 2]
Generated description
Terminal 2 is one of the passenger terminals at Václav Havel Airport Prague, primarily serving flights within the Schengen Area.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Terminal 2 Target entity description: Terminal 2 is one of the passenger terminals at Václav Havel Airport Prague, primarily serving flights within the Schengen Area.
-
A.
Terminal 2
chosen
Terminal 2 is a passenger terminal at Václav Havel Airport Prague primarily serving flights within the Schengen Area.
-
B.
Terminal 2
Terminal 2 is one of the main passenger terminals at Helsinki Airport, serving as a hub for many international and Schengen flights with modern facilities and services.
-
C.
Terminal 2
Terminal 2 is one of the main passenger terminals at Vienna International Airport, serving as a hub for check-in, security, and boarding operations for various airlines.
-
D.
Terminal 2
Terminal 2 is one of the main passenger terminals at Hamburg Airport, handling check-in, security, and boarding for various domestic and international flights.
-
E.
Terminal 2
Terminal 2 is one of the main passenger terminals at Xi'an Xianyang International Airport, handling a significant share of the airport's domestic and regional flights.
- F. None of above.
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d886c7b1e481908c3766dfa8c13458 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3ca3f1a2c8190a512ccc09a080eb4 |
completed | April 18, 2026, 6:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00cfd0ff2881908686678daab46664 |
completed | May 10, 2026, 6:34 p.m. |
| NEDg | Description generation | batch_6a00d0a0852c8190991af93d50fa2216 |
completed | May 10, 2026, 6:38 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00d14b83d88190b3dbc124d5b33029 |
completed | May 10, 2026, 6:41 p.m. |
Created at: April 10, 2026, 5:30 a.m.