Triple
T14148577
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terminal 2B |
E350614
|
entity |
| Predicate | belongsTo |
P35
|
FINISHED |
| Object | Terminal 2 complex |
E342707
|
NE FINISHED |
How this triple was built (2 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 complex | Statement: [Terminal 2B, belongsTo, Terminal 2 complex]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Terminal 2 complex Context triple: [Terminal 2B, belongsTo, Terminal 2 complex]
-
A.
Terminal 2 complex
chosen
Terminal 2 complex is a major multi-terminal passenger facility at Paris Charles de Gaulle Airport that groups several interconnected sub-terminals and services.
-
B.
Terminal 3
Terminal 3 is a major domestic passenger terminal at San Francisco International Airport, primarily serving United Airlines and its partners.
-
C.
Terminal 3
Terminal 3 is one of the passenger terminals at Adolfo Suárez Madrid–Barajas Airport in Madrid, Spain, serving as part of the airport’s main complex for domestic and international flights.
-
D.
Terminal 3
Terminal 3 is a major passenger terminal facility at Guangzhou Baiyun International Airport, serving as one of its primary hubs for domestic and international air travel.
-
E.
Terminal 3
Terminal 3 is a modern passenger terminal at Soekarno–Hatta International Airport in Indonesia, serving as a major hub for both domestic and international flights.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d827865f608190b311820428ae027b |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61237ef481909374c1f68a2370b7 |
completed | April 14, 2026, 3:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcdf205c788190920b5055f9fe63a8 |
completed | May 7, 2026, 6:51 p.m. |
Created at: April 10, 2026, 12:55 a.m.