Triple
T1883583
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Martínez |
E39908
|
entity |
| Predicate | hasTypicalGenderAssociation |
P34349
|
FINISHED |
| Object | family name used by all genders |
—
|
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: family name used by all genders | Statement: [Martínez, hasTypicalGenderAssociation, family name used by all genders]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalGenderAssociation Context triple: [Martínez, hasTypicalGenderAssociation, family name used by all genders]
-
A.
genderStereotypingRecognizedAs
Indicates that a particular belief, behavior, or representation is acknowledged or classified as a form of gender stereotyping.
-
B.
hasGenderInSomeTraditions
Indicates that, in at least some cultural, religious, or historical traditions, the subject is regarded as having a specific gender.
-
C.
hasGenderFocus
Indicates that something is specifically concerned with, oriented toward, or primarily addressing a particular gender or gender-related issues.
-
D.
hasGenderDistinction
Indicates that a relationship, classification, or linguistic form differentiates entities based on gender categories.
-
E.
genderCategories
Indicates the classification of an entity into one or more gender-related categories or identities.
- 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_69a88633e4fc8190b7eb40463e048ec5 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb4f53f408190ae30e1a12721e7d7 |
completed | March 7, 2026, 5:17 a.m. |
| PD | Predicate disambiguation | batch_69abafe497a88190a1da6af2888b71b4 |
completed | March 7, 2026, 4:56 a.m. |
| PDg | Predicate description generation | batch_69abb4f3fb9481908b54506dc2836124 |
completed | March 7, 2026, 5:17 a.m. |
Created at: March 4, 2026, 7:34 p.m.