Triple
T36046905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United Airlines Flight 553 |
E1042695
|
entity |
| Predicate | becameSubjectOf |
P35270
|
FINISHED |
| Object | political controversy |
—
|
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: political controversy | Statement: [United Airlines Flight 553, becameSubjectOf, political controversy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: becameSubjectOf Context triple: [United Airlines Flight 553, becameSubjectOf, political controversy]
-
A.
hasBeenSubjectOf
chosen
Indicates that an entity has previously been the focus or target of a particular action, process, or investigation.
-
B.
mayBeSubjectOf
Indicates that an entity has the potential or possibility to serve as the subject in a given relation, event, or statement.
-
C.
immediateSubjectOf
Indicates that one entity is the direct grammatical subject of another entity (typically a clause, phrase, or verb), without any intervening subject relations.
-
D.
subjectOfEvent
Indicates that an entity participates in or is involved in a particular event as one of its primary actors or focal points.
-
E.
notableStorySubject
Indicates that the subject is a prominent or central topic, character, or element within a particular story or narrative.
- 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_69f76e2e41f8819091f9fb0536920fec |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7b2c771108190adeec151daad5dab |
completed | May 3, 2026, 8:40 p.m. |
| PD | Predicate disambiguation | batch_69f7b1bad2e88190963ab4ee5d4f2038 |
completed | May 3, 2026, 8:36 p.m. |
Created at: May 3, 2026, 4:07 p.m.