Triple
T9468470
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | British Airways Concorde Room |
E228332
|
entity |
| Predicate | locatedInTerminal |
P40
|
FINISHED |
| Object | Terminal 7 |
E2890
|
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 7 | Statement: [British Airways Concorde Room, locatedInTerminal, Terminal 7]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Terminal 7 Context triple: [British Airways Concorde Room, locatedInTerminal, Terminal 7]
-
A.
Terminal 7
Terminal 7 is one of the passenger terminals at Los Angeles International Airport, primarily serving United Airlines and its partner carriers.
-
B.
Terminal 7
chosen
Terminal 7 is one of the passenger terminals at John F. Kennedy International Airport in New York City, historically serving several international airlines.
-
C.
Terminal 6
Terminal 6 is one of the passenger terminals at Los Angeles International Airport, serving a mix of domestic and some international flights for several major airlines.
-
D.
Terminal 1
Terminal 1 is a main passenger terminal at Marseille Provence Airport, serving as a hub for check-in, security, boarding, and arrivals for many of the airport’s flights.
-
E.
Terminal 1
Terminal 1 is one of the main passenger terminals at Munich Airport, handling a significant share of its international and domestic 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_69ca846fee388190a6ec273fd644b88b |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7fdf604481909bf7d7d477230ca3 |
completed | April 1, 2026, 8:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d122c45ae88190a43d70300bed98da |
completed | April 4, 2026, 2:40 p.m. |
Created at: March 30, 2026, 7:53 p.m.