Triple
T26533002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Queen of Knits |
E670869
|
entity |
| Predicate | industryOfPersonReferredTo |
P115650
|
FINISHED |
| Object | fashion industry |
—
|
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: fashion industry | Statement: [Queen of Knits, industryOfPersonReferredTo, fashion industry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: industryOfPersonReferredTo Context triple: [Queen of Knits, industryOfPersonReferredTo, fashion industry]
-
A.
employerOfNotablePerson
Indicates that an entity serves or has served as the employer of a person who is considered notable.
-
B.
characterIndustry
chosen
Indicates a relationship where a character is associated with, works in, or is otherwise linked to a particular industry or economic sector.
-
C.
refersToProfession
Indicates that one entity is being referenced specifically in terms of its profession or occupational role in relation to another entity.
-
D.
occupationType
Indicates the specific kind or category of work, profession, or role that an entity performs or holds.
-
E.
refersToPersonKnownFor
Indicates that one entity makes reference to a person who is notable or recognized for some specific role, achievement, or characteristic.
- 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_69eeb31ea1e08190b9ff43cf9bc25bf8 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f6352fdb788190b9bad30243690743 |
completed | May 2, 2026, 5:32 p.m. |
| PD | Predicate disambiguation | batch_69f631850ae08190a0ba51e4f1e4ccb3 |
completed | May 2, 2026, 5:16 p.m. |
Created at: April 27, 2026, 1:36 a.m.