Triple
T31673051
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | College of the Holy Cross |
E808322
|
entity |
| Predicate | formerGenderPolicy |
P14517
|
FINISHED |
| Object | men-only college |
—
|
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: men-only college | Statement: [College of the Holy Cross, formerGenderPolicy, men-only college]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formerGenderPolicy Context triple: [College of the Holy Cross, formerGenderPolicy, men-only college]
-
A.
hasGenderPolicy
Indicates that an entity has adopted, implemented, or is governed by a specific policy related to gender issues or gender equality.
-
B.
formerGenderAdmission
chosen
Indicates that an institution previously admitted a particular gender but no longer does so.
-
C.
governsGender
Indicates that one entity determines or constrains the gender classification or gender-related properties of another entity.
-
D.
genderNeutralSince
Indicates that an entity has been considered gender-neutral starting from a specific point in time.
-
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_69f348dcf5d48190ac25b1365ae717a8 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69ff409ff5548190849c2d50e99bd807 |
completed | May 9, 2026, 2:11 p.m. |
| PD | Predicate disambiguation | batch_69ff401a5e188190a72f945e910b4a6c |
completed | May 9, 2026, 2:09 p.m. |
Created at: April 30, 2026, 11:01 p.m.