Triple
T172501
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AA |
E3505
|
entity |
| Predicate | usedToConstruct |
P3565
|
FINISHED |
| Object | flight numbers for American Airlines |
—
|
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: flight numbers for American Airlines | Statement: [AA, usedToConstruct, flight numbers for American Airlines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedToConstruct Context triple: [AA, usedToConstruct, flight numbers for American Airlines]
-
A.
usedToInfer
Indicates that one entity serves as a basis or source from which another entity is logically derived or concluded.
-
B.
constructedAs
chosen
Indicates that one entity is built, formed, or created in the manner, structure, or configuration specified by another entity.
-
C.
isUsedAs
Indicates that one entity serves a particular function, role, or purpose as another entity.
-
D.
usedFor
Indicates that one entity serves a purpose, function, or role in accomplishing, enabling, or supporting another entity or activity.
-
E.
usedOn
Indicates that one entity is applied to, operated on, or otherwise utilized in relation to another entity.
- 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_69a25374990081909766d30c79a18e0e |
completed | Feb. 28, 2026, 2:31 a.m. |
| NER | Named-entity recognition | batch_69a25a3f9d188190aacf5791273e2c65 |
completed | Feb. 28, 2026, 3 a.m. |
| PD | Predicate disambiguation | batch_69a25667717c8190bac5108366e2178d |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:39 a.m.