Triple
T5478601
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U.S. statesman |
E123415
|
entity |
| Predicate | genderedTerm |
P17779
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [U.S. statesman, genderedTerm, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genderedTerm Context triple: [U.S. statesman, genderedTerm, yes]
-
A.
genderUsage
Indicates how a particular gender is applied, referenced, or treated within a given context or system.
-
B.
genderSignificance
Indicates the relevance or impact that an entity’s gender has within a particular context, relationship, or interpretation.
-
C.
genderCategories
Indicates the classification of an entity into one or more gender-related categories or identities.
-
D.
genderedFormOf
chosen
Indicates that one term is a gender-specific variant or inflected form corresponding to another, more neutral or differently gendered term.
-
E.
genderStereotypingRecognizedAs
Indicates that a particular belief, behavior, or representation is acknowledged or classified as a form of gender stereotyping.
- 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_69bd4648883481909e9775d43300c5fa |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd9247a16c8190ac5a02534da48853 |
completed | March 20, 2026, 6:30 p.m. |
| PD | Predicate disambiguation | batch_69bd91a58c448190904964a439045e05 |
completed | March 20, 2026, 6:27 p.m. |
Created at: March 20, 2026, 2:09 p.m.