Triple
T32425311
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ama diving tradition |
E828560
|
entity |
| Predicate | alsoIncludesGenderOfDivers |
P174066
|
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: [Ama diving tradition, alsoIncludesGenderOfDivers, male]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alsoIncludesGenderOfDivers Context triple: [Ama diving tradition, alsoIncludesGenderOfDivers, male]
-
A.
includesBothGenders
Indicates that the referenced group, set, or category contains members of both male and female genders.
-
B.
hasNumberOfGenders
Indicates the relationship that specifies how many distinct genders are associated with or recognized for a given entity.
-
C.
hasGenderVariant
Indicates that one entity is a gender-specific form or variant of another entity.
-
D.
genderOfCompetitors
Indicates the gender category or composition of the participants involved in a competition or competitive event.
-
E.
hasGenderDivisions
Indicates that something is organized, classified, or separated into groups based on gender.
- F. None of above. chosen
Provenance (4 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_69f3491b28bc8190b75cea7a507f337b |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c286ac288190843dac21651babd0 |
completed | May 3, 2026, 3:35 a.m. |
| PD | Predicate disambiguation | batch_69f6ba6eb32c8190bf405b2011fa48f7 |
completed | May 3, 2026, 3:01 a.m. |
| PDg | Predicate description generation | batch_69f6bb344bb48190a8089f29c0063ded |
completed | May 3, 2026, 3:04 a.m. |
Created at: May 1, 2026, 12:54 a.m.