Triple
T13357380
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meteor F.8 |
E318727
|
entity |
| Predicate | operatorRoleInKorea |
P109602
|
FINISHED |
| Object | fighter-bomber |
—
|
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: fighter-bomber | Statement: [Meteor F.8, operatorRoleInKorea, fighter-bomber]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operatorRoleInKorea Context triple: [Meteor F.8, operatorRoleInKorea, fighter-bomber]
-
A.
roleInKoreanWar
Indicates the specific function, position, or involvement an entity had during the Korean War.
-
B.
roleInOperation
Indicates that an entity holds a specific function, duty, or position within a particular operation or activity.
-
C.
roleInPhilippines
Indicates that an entity holds or has held an official or notable role, position, or function within the Philippines.
-
D.
employedRole
Indicates that an entity holds or performs a specific role or position within an employment or work context.
-
E.
possibleRole
Indicates that an entity is capable of or eligible to serve in a particular role or function in a given context.
- F. None of above. chosen
Provenance (4 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_69d806b7bbac8190b85278c87fa7aff3 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69da62887e588190bd7241c720a112a2 |
completed | April 11, 2026, 3:02 p.m. |
| PD | Predicate disambiguation | batch_69d9a02c9abc8190b328e7bae747bfc5 |
completed | April 11, 2026, 1:13 a.m. |
| PDg | Predicate description generation | batch_69dadcce5a808190847f2a7833b67a5a |
completed | April 11, 2026, 11:44 p.m. |
Created at: April 9, 2026, 9:32 p.m.