Triple
T3924020
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terminal 3 (O'Hare) |
E93228
|
entity |
| Predicate | primarilyServes |
P17274
|
FINISHED |
| Object | American Airlines hub operations at O'Hare |
—
|
LITERAL 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: American Airlines hub operations at O'Hare | Statement: [Terminal 3 (O'Hare), primarilyServes, American Airlines hub operations at O'Hare]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primarilyServes Context triple: [Terminal 3 (O'Hare), primarilyServes, American Airlines hub operations at O'Hare]
-
A.
primaryServes
Indicates that one entity’s main or principal function is to serve, support, or provide service to another entity.
-
B.
servesMostly
chosen
Indicates that one entity primarily functions to serve, support, or cater to another entity, more than to any other.
-
C.
servesOn
Indicates that one entity performs duties, functions, or holds a role as a member within another entity, such as a group, body, or organization.
-
D.
intendedToServe
Indicates that one entity was designed, planned, or purposed specifically to benefit, assist, or fulfill the needs of another entity.
-
E.
servesSuburbsOf
Indicates that a service, route, or facility provides coverage or support to the suburban areas associated with a particular city or region.
- F. None of above.
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_69aed96bfa1081908f7b30f2c647dee6 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69aeed7dacdc8190854ebc13db2d24bc |
completed | March 9, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69aee7609c4081908000ce12ae827c3f |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:23 p.m.