Triple
T4677960
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A. M. Barnard |
E103726
|
entity |
| Predicate | genderOfAuthor |
P9920
|
FINISHED |
| Object | female |
—
|
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: female | Statement: [A. M. Barnard, genderOfAuthor, female]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genderOfAuthor Context triple: [A. M. Barnard, genderOfAuthor, female]
-
A.
hasAuthorGender
chosen
Indicates that an entity (such as a work or publication) is associated with an author of a specified gender.
-
B.
genderOfEponym
Indicates the gender of the person after whom something (such as a place, object, or concept) is named.
-
C.
creatorSexOrGender
Indicates that the specified sex or gender is the sex or gender of the creator of the referenced work or entity.
-
D.
genderRule
Indicates a rule or constraint that determines how gender-related properties or classifications should be assigned or interpreted in a given context.
-
E.
hasGenderOfPerson
Indicates that a person is associated with a specific gender classification.
- 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_69bd43dda32c8190938b37744ca270fc |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd67c9c3c08190a6c4944cdd1362a8 |
completed | March 20, 2026, 3:29 p.m. |
| PD | Predicate disambiguation | batch_69bd6217e0088190836570522e324dc6 |
completed | March 20, 2026, 3:04 p.m. |
Created at: March 20, 2026, 1:16 p.m.