Triple
T325193
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KLAX |
E6499
|
entity |
| Predicate | hasTerminal |
P182
|
FINISHED |
| Object | Terminal 3 |
E14748
|
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 3 | Statement: [KLAX, hasTerminal, Terminal 3]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Terminal 3 Context triple: [KLAX, hasTerminal, Terminal 3]
-
A.
Terminal 3
Terminal 3 is one of the passenger terminals at Manchester Airport, serving a range of domestic and international flights with dedicated check-in, security, and boarding facilities.
-
B.
Terminal 3
chosen
Terminal 3 is one of the passenger terminals at Los Angeles International Airport, serving as a hub for several domestic and international airline operations.
-
C.
Terminal 3
Terminal 3 is one of the passenger terminals at Paris Charles de Gaulle Airport, primarily serving low-cost and charter airlines.
-
D.
Terminal 3
Terminal 3 is one of the main passenger terminals at Phoenix Sky Harbor International Airport, serving as a hub for multiple domestic and some international flights with modernized facilities and amenities.
-
E.
Terminal 3
Terminal 3 is the main international passenger terminal at José Martí International Airport in Havana, Cuba, handling most long-haul and major airline operations.
- 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_69a2e7933d6c8190bb2592ad13286ef2 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2ea959f9c819084602b8a1b5e66dd |
completed | Feb. 28, 2026, 1:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3d4e03a608190820e3bef93158a15 |
completed | March 1, 2026, 5:55 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.