Triple
T23881301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 辛丑条约 |
E600207
|
entity |
| Predicate | 历史背景 |
P43371
|
FINISHED |
| Object | 义和团运动 |
—
|
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: 义和团运动 | Statement: [辛丑条约, 历史背景, 义和团运动]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 历史背景 Context triple: [辛丑条约, 历史背景, 义和团运动]
-
A.
historicalBackground
chosen
Indicates that one entity provides contextual historical information or circumstances that help explain the origin, development, or significance of another entity.
-
B.
historicalReason
Indicates that one entity exists, occurs, or is justified because of causes, events, or circumstances rooted in the past of another entity.
-
C.
shareHistoricalContextAs
Indicates that two or more entities are associated with or understood within the same historical background, period, or circumstances.
-
D.
historicalOrigin
Indicates the relationship by which one entity serves as the source, origin, or starting point in history for another entity.
-
E.
hasHistoricalContext
Indicates that something is related to, influenced by, or best understood in light of specific past events, conditions, or time periods.
- 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_69e295318e148190b9979d8fc02e168f |
completed | April 17, 2026, 8:16 p.m. |
| NER | Named-entity recognition | batch_69f1cc05e4d48190864fc47bdffa4ca9 |
completed | April 29, 2026, 9:14 a.m. |
| PD | Predicate disambiguation | batch_69f1614a65a88190bde1efb368a151e4 |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:24 p.m.