Triple
T3493371
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Doctor of the Church |
E73787
|
entity |
| Predicate | hasGenderDiversity |
P14432
|
FINISHED |
| Object | includes male saints |
—
|
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: includes male saints | Statement: [Doctor of the Church, hasGenderDiversity, includes male saints]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGenderDiversity Context triple: [Doctor of the Church, hasGenderDiversity, includes male saints]
-
A.
hasNumberOfGenders
Indicates the relationship that specifies how many distinct genders are associated with or recognized for a given entity.
-
B.
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.
-
C.
diversity
chosen
Indicates the degree to which a set of entities differs along one or more dimensions such as type, attributes, or characteristics.
-
D.
supportsDiversity
Indicates that one entity actively promotes, encourages, or upholds diversity in or for another entity.
-
E.
hasDiverseStudentBody
Indicates that an educational institution’s student population includes a wide range of backgrounds, characteristics, or identities.
- 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_69ad85cca8d4819088494e9f3340fab5 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbbad51648190b756ad621d6d7df0 |
completed | March 8, 2026, 6:10 p.m. |
| PD | Predicate disambiguation | batch_69adae0b34908190b2bb5766a2231f7a |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:18 p.m.