Triple
T5064578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chatham University |
E114111
|
entity |
| Predicate | undergraduateGenderPolicy |
P14517
|
FINISHED |
| Object | historically women-only |
—
|
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: historically women-only | Statement: [Chatham University, undergraduateGenderPolicy, historically women-only]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: undergraduateGenderPolicy Context triple: [Chatham University, undergraduateGenderPolicy, historically women-only]
-
A.
hasGenderPolicy
Indicates that an entity has adopted, implemented, or is governed by a specific policy related to gender issues or gender equality.
-
B.
admissionGender
Indicates the gender-based criteria or classification applied in the context of admission or entry decisions.
-
C.
formerGenderAdmission
chosen
Indicates that an institution previously admitted a particular gender but no longer does so.
-
D.
governsGender
Indicates that one entity determines or constrains the gender classification or gender-related properties of another entity.
-
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_69bd443c0c8c81908663b77afb28e165 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7478f7988190bc0473e8af055147 |
completed | March 20, 2026, 4:23 p.m. |
| PD | Predicate disambiguation | batch_69bd715622b48190a3e8e49a5ef62b4a |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:38 p.m.