Triple
T27051546
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xun school |
E684784
|
entity |
| Predicate | roleTypeSpecialization |
P100451
|
FINISHED |
| Object | huadan roles |
—
|
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: huadan roles | Statement: [Xun school, roleTypeSpecialization, huadan roles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleTypeSpecialization Context triple: [Xun school, roleTypeSpecialization, huadan roles]
-
A.
positionSpecialization
Indicates that one position is a more specialized or focused variant of another, broader position.
-
B.
roleInSpecification
Indicates that an entity participates in a specification with a particular role or function within that specification.
-
C.
labelSpecialization
Indicates that one label is a more specific or specialized version of another label within a labeling or classification system.
-
D.
specialRole
Indicates that an entity holds a distinctive or exceptional function, status, or responsibility in relation to another entity or context.
-
E.
portrayedAsSpecialization
chosen
Indicates that one entity is depicted or represented as a specialized or more specific version 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_69ef14829fac8190914bef9ecc3005d7 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69f6383625cc8190aa223d8ef655743c |
completed | May 2, 2026, 5:45 p.m. |
| PD | Predicate disambiguation | batch_69f63709e4848190b5cf322e06b23fb6 |
completed | May 2, 2026, 5:40 p.m. |
Created at: April 27, 2026, 8:14 a.m.