Triple
T11081755
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zhang Zhidong |
E262010
|
entity |
| Predicate | positionOnBoxerRebellion |
P97113
|
FINISHED |
| Object | opposed anti-foreign violence |
—
|
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: opposed anti-foreign violence | Statement: [Zhang Zhidong, positionOnBoxerRebellion, opposed anti-foreign violence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: positionOnBoxerRebellion Context triple: [Zhang Zhidong, positionOnBoxerRebellion, opposed anti-foreign violence]
-
A.
positionWithinConfederacy
Indicates that one entity holds a specific role, rank, or status within a confederated group or alliance of entities.
-
B.
locationDuringConflict
Indicates that an entity is situated in a specific place for some or all of the duration of a particular conflict or hostilities.
-
C.
positionInBattle
Indicates the specific role or placement an entity occupies within the formation or structure of a battle.
-
D.
facedRebellionBy
Indicates that an entity experienced opposition or an uprising initiated by another entity.
-
E.
positionOnCivilDisobedience
Indicates a stance or viewpoint an entity holds regarding the legitimacy, morality, or use of civil disobedience.
- 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_69d6aa9983c08190b0ef61603b69feac |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d799985650819089b2c0f35a212414 |
completed | April 9, 2026, 12:20 p.m. |
| PD | Predicate disambiguation | batch_69d74415403c81909778bcd829e8832e |
completed | April 9, 2026, 6:15 a.m. |
| PDg | Predicate description generation | batch_69d750ca52ec8190a559432a5de106fd |
completed | April 9, 2026, 7:10 a.m. |
Created at: April 8, 2026, 9:27 p.m.