Triple
T3679103
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Huang Xingguo |
E78066
|
entity |
| Predicate | reasonForInvestigation |
P24494
|
FINISHED |
| Object | serious disciplinary violations |
—
|
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: serious disciplinary violations | Statement: [Huang Xingguo, reasonForInvestigation, serious disciplinary violations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reasonForInvestigation Context triple: [Huang Xingguo, reasonForInvestigation, serious disciplinary violations]
-
A.
typeOfInvestigation
Indicates the specific kind or category of investigation being conducted or referred to in the relationship.
-
B.
reasonForStay
Indicates the underlying cause, purpose, or circumstance that explains why an entity remains or is staying in a particular place or situation.
-
C.
reasonForUse
Indicates that one entity specifies the justification, purpose, or motivation for using another entity.
-
D.
statedReason
chosen
Indicates that one entity expresses or provides another entity as the explanation, justification, or motive for an action, event, or claim.
-
E.
reasonForWork
Indicates that one entity specifies the motivation, cause, or purpose behind another entity’s work or activity.
- 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_69ad85e18c1c8190be8aafb227f39f48 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc49039308190b33082e2b58aa5cf |
completed | March 8, 2026, 6:48 p.m. |
| PD | Predicate disambiguation | batch_69adb84be1fc81909721c871babb4633 |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:25 p.m.