Triple
T10953332
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zhang Xueliang |
E258777
|
entity |
| Predicate | detentionStartYear |
P31117
|
FINISHED |
| Object | 1936 |
—
|
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: 1936 | Statement: [Zhang Xueliang, detentionStartYear, 1936]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: detentionStartYear Context triple: [Zhang Xueliang, detentionStartYear, 1936]
-
A.
dateOfImprisonmentStart
Indicates the date on which an entity’s period of imprisonment begins.
-
B.
imprisonmentYear
chosen
Indicates the specific year in which an entity was imprisoned or placed into custody.
-
C.
dateOfNotableIncarceration
Indicates the specific date on which an entity began a notable or historically significant period of incarceration.
-
D.
detainedUntil
Indicates that an entity is held in custody or confinement up to a specified time or until a particular condition is met.
-
E.
detainedFor
Indicates that one entity is being held in custody or confinement because of, or as a consequence of, another entity (such as a reason, charge, or event).
- 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_69d6aa88500c819097d7032ca578e74f |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d770fe4cfc81909032296c31e077f0 |
completed | April 9, 2026, 9:27 a.m. |
| PD | Predicate disambiguation | batch_69d72e874f48819096ffa878f90c7d5b |
completed | April 9, 2026, 4:43 a.m. |
Created at: April 8, 2026, 9:23 p.m.