Triple
T32829409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kyle |
E839646
|
entity |
| Predicate | hasTraditionalGenderAssociation |
P34349
|
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: [Kyle, hasTraditionalGenderAssociation, male]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTraditionalGenderAssociation Context triple: [Kyle, hasTraditionalGenderAssociation, male]
-
A.
hasTypicalGenderAssociation
chosen
Indicates that one entity is commonly or culturally associated with a particular gender more than with other genders.
-
B.
hasGenderInSomeTraditions
Indicates that, in at least some cultural, religious, or historical traditions, the subject is regarded as having a specific gender.
-
C.
hasAlternativeGenderUsage
Indicates that an entity is used with a different or non-standard gender form in certain contexts or usages.
-
D.
hasGrammaticalGender
Indicates that one entity assigns or possesses a specific grammatical gender in relation to another entity (such as a word, phrase, or linguistic unit).
-
E.
genderRoleAssociation
Indicates an association between a gender and a particular social role, behavior, or expectation.
- 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_69f3493f22f88190ae6dd4bc15b6cf8d |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69ff21cbd9108190a52c0ba42004c669 |
completed | May 9, 2026, noon |
| PD | Predicate disambiguation | batch_69ff1faea91881908c626c70bca5100a |
completed | May 9, 2026, 11:51 a.m. |
Created at: May 1, 2026, 1:16 a.m.