Triple
T356569
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chuck Yeager |
E7554
|
entity |
| Predicate | wasPrisonerOfWar |
P6764
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Chuck Yeager, wasPrisonerOfWar, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasPrisonerOfWar Context triple: [Chuck Yeager, wasPrisonerOfWar, true]
-
A.
prisonersOfWar
chosen
Indicates a relationship where certain individuals are held in custody by an enemy during an armed conflict as prisoners of war.
-
B.
wasImprisonedIn
Indicates that an entity was held in confinement or incarcerated at a particular place or facility.
-
C.
sideInWorldWarII
Indicates that an entity was aligned with or participated on a particular side during World War II.
-
D.
legalStatusAfterWar
Indicates the legal condition or classification assigned to an entity as a consequence of, or following the conclusion of, a war or armed conflict.
-
E.
wasBombedDuring
Indicates that an entity was subjected to a bombing attack during a specified event or time period.
- 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_69a2e7e696948190bebc966535995e45 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ebaf0c9881909313f98818e7fa58 |
completed | Feb. 28, 2026, 1:20 p.m. |
| PD | Predicate disambiguation | batch_69a2e959ce948190a201c017eecb7c95 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.