Triple
T2360810
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zhang Xueliang |
E47265
|
entity |
| Predicate | yearsUnderHouseArrest |
P8398
|
FINISHED |
| Object | over 50 years |
—
|
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: over 50 years | Statement: [Zhang Xueliang, yearsUnderHouseArrest, over 50 years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: yearsUnderHouseArrest Context triple: [Zhang Xueliang, yearsUnderHouseArrest, over 50 years]
-
A.
placedUnderHouseArrest
Indicates that an authority has confined an entity to a specified residence, restricting their freedom of movement as a form of legal or disciplinary control.
-
B.
servedPrisonTime
Indicates that an entity has spent a period of time incarcerated in prison as a consequence of a legal sentence.
-
C.
imprisonedFor
Indicates that one entity is held in detention or jail as a consequence of, or in connection with, a specific reason, action, or offense committed by another entity or itself.
-
D.
durationOfImprisonment
chosen
Indicates the length of time that an entity is or was held in imprisonment.
-
E.
hasBeenImprisonedBy
Indicates that one entity has been confined or incarcerated under the authority or control of 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_69a88a1a4a6081908645b0f2914521ab |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abc722ac3c819091f4316a4a166a77 |
completed | March 7, 2026, 6:35 a.m. |
| PD | Predicate disambiguation | batch_69abc599b92c819093d9e15d4437705d |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:55 p.m.