Triple
T8112370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wells College |
E189385
|
entity |
| Predicate | historicalGenderAdmissionPolicy |
P14517
|
FINISHED |
| Object | women-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: women-only college | Statement: [Wells College, historicalGenderAdmissionPolicy, women-only college]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: historicalGenderAdmissionPolicy Context triple: [Wells College, historicalGenderAdmissionPolicy, women-only college]
-
A.
formerGenderAdmission
chosen
Indicates that an institution previously admitted a particular gender but no longer does so.
-
B.
admissionGender
Indicates the gender-based criteria or classification applied in the context of admission or entry decisions.
-
C.
hasGenderPolicy
Indicates that an entity has adopted, implemented, or is governed by a specific policy related to gender issues or gender equality.
-
D.
hasGenderHistory
Indicates that an entity has undergone or experienced a change or transition in gender over time.
-
E.
admittedWomen
Indicates that an entity allowed or accepted women into a place, group, institution, or event.
- 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_69ca82baad008190ab2859712b9b1607 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb4664fef881908b0dc7b158aca398 |
completed | March 31, 2026, 3:58 a.m. |
| PD | Predicate disambiguation | batch_69cb368e7f4c81909aabd7716f0de79d |
completed | March 31, 2026, 2:50 a.m. |
Created at: March 30, 2026, 5:32 p.m.