Triple
T23881326
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 辛丑条约 |
E600207
|
entity |
| Predicate | 政治影响 |
P1784
|
FINISHED |
| Object | 严重损害中国主权 |
—
|
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: 严重损害中国主权 | Statement: [辛丑条约, 政治影响, 严重损害中国主权]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 政治影响 Context triple: [辛丑条约, 政治影响, 严重损害中国主权]
-
A.
politicalRepercussion
chosen
Indicates that an action, event, or decision leads to consequences or fallout within a political context, such as shifts in power, public opinion, or policy.
-
B.
俗语影响
Indicates that a proverb or common saying exerts an influence on someone or something, such as their thoughts, behavior, or decisions.
-
C.
politicalInfluenceIn
Indicates that an entity exerts or holds political influence within a specified place, jurisdiction, or political context.
-
D.
politicalPowerInfluencedBy
Indicates that the extent or nature of an entity’s political power is shaped, affected, or determined by another entity or factor.
-
E.
politicalInfluenceStatus
Indicates the degree or state of one entity’s ability to affect or shape another entity’s political decisions, actions, or outcomes.
- 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.