Triple
T4375982
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terminal 2G |
E99006
|
entity |
| Predicate | partOf |
P40
|
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 2G, partOf, Terminal 2 complex]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Terminal 2 complex Context triple: [Terminal 2G, partOf, 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 one of the main passenger terminals at Leonardo da Vinci–Fiumicino Airport in Rome, handling a large share of the airport’s international and domestic flights.
-
C.
Terminal 3
Terminal 3 is a passenger terminal at Cincinnati/Northern Kentucky International Airport serving airline operations and traveler services.
-
D.
Terminal 3
Terminal 3 is Haneda Airport’s international terminal in Tokyo, serving as a major hub for overseas flights and passenger services.
-
E.
Terminal 3
Terminal 3 is one of the passenger terminals at Mehrabad International Airport in Tehran, serving domestic air traffic within Iran.
- 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_69b3454ea8f48190a49c2436624d6ef6 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3523d4e888190b4367ed6aa17d463 |
completed | March 12, 2026, 11:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5e5162d5081909e7d8813907e25a6 |
completed | March 14, 2026, 10:45 p.m. |
Created at: March 12, 2026, 11:18 p.m.