Triple
T37570198
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ashipa |
E934667
|
entity |
| Predicate | titleHolderGenderTraditionally |
P34342
|
FINISHED |
| Object | male |
—
|
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: male | Statement: [Ashipa, titleHolderGenderTraditionally, male]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: titleHolderGenderTraditionally Context triple: [Ashipa, titleHolderGenderTraditionally, male]
-
A.
titleHolderSex
Indicates the biological or identified sex of the person who holds a particular title.
-
B.
genderOfTypicalHolder
chosen
Indicates the gender that is most commonly associated with or typical of the usual holder of something.
-
C.
genderOfFirstHolder
Indicates that the relationship specifies the gender of the first entity that holds or possesses something in the described context.
-
D.
namedForGender
Indicates that one entity is named in a way that reflects or is derived from a particular gender or gender-related characteristic of another entity.
-
E.
successorTitleGender
Indicates the gender associated with the person who succeeds another in a given title or position.
- 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_69f76ecd99148190be327e391a70f5b6 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fff4530f908190afe9387f732c2b7e |
completed | May 10, 2026, 2:58 a.m. |
| PD | Predicate disambiguation | batch_69fff3c01a64819091196875b0c88607 |
completed | May 10, 2026, 2:56 a.m. |
Created at: May 3, 2026, 4:17 p.m.