Triple
T6443610
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alliluev |
E138284
|
entity |
| Predicate | commonGenderUsage |
P15656
|
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: [Alliluev, commonGenderUsage, male]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonGenderUsage Context triple: [Alliluev, commonGenderUsage, male]
-
A.
genderUsage
chosen
Indicates how a particular gender is applied, referenced, or treated within a given context or system.
-
B.
usesGenderAccurateLanguage
Indicates that the language employed in the context correctly reflects and respects the gender identities of the entities referenced.
-
C.
usedByGender
Indicates that something is utilized, applied, or engaged in by entities of a specified gender.
-
D.
genderSignificance
Indicates the relevance or impact that an entity’s gender has within a particular context, relationship, or interpretation.
-
E.
hasGenderNeutrality
Indicates that something (such as a term, form, or expression) is neutral with respect to gender and does not specify or imply any particular gender.
- 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_69c008aa61ac8190bc96715ed79fe2d8 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0698b030481908b7bb4e16a8b3339 |
completed | March 22, 2026, 10:13 p.m. |
| PD | Predicate disambiguation | batch_69c060faaf248190bbdc8ff909c8777a |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:46 p.m.