Triple
T4191559
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KORD |
E89047
|
entity |
| Predicate | hasTerminal |
P182
|
FINISHED |
| Object | Terminal 5 |
E93759
|
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 5 | Statement: [KORD, hasTerminal, Terminal 5]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Terminal 5 Context triple: [KORD, hasTerminal, Terminal 5]
-
A.
Terminal 5
chosen
Terminal 5 is the international terminal at Chicago O'Hare International Airport, serving most of the airport’s non-domestic and many foreign-flag carriers.
-
B.
Terminal 5
Terminal 5 is a major passenger terminal at John F. Kennedy International Airport in New York City, known for serving as the primary hub for JetBlue Airways.
-
C.
Terminal 5
Terminal 5 is a major, modern passenger terminal at London Heathrow Airport primarily serving British Airways and Iberia flights.
-
D.
Terminal 5
Terminal 5 is a dedicated passenger terminal at Rome’s Leonardo da Vinci–Fiumicino Airport, primarily used for certain international and long-haul flights.
-
E.
Terminal 5
Terminal 5 is a passenger terminal facility at Mehrabad International Airport in Tehran, 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_69aed9569a4481908b6c1fcec2a11e21 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af034169f88190a8eb170ba6008b79 |
completed | March 9, 2026, 5:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5a849cdac8190b12ac2a0e42c3b53 |
completed | March 14, 2026, 6:26 p.m. |
Created at: March 9, 2026, 3:46 p.m.