Triple
T13825053
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grand Orient de France |
E332228
|
entity |
| Predicate | acceptsWomen |
P12173
|
FINISHED |
| Object | has progressively opened or associated with women’s participation in some structures |
—
|
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: has progressively opened or associated with women’s participation in some structures | Statement: [Grand Orient de France, acceptsWomen, has progressively opened or associated with women’s participation in some structures]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: acceptsWomen Context triple: [Grand Orient de France, acceptsWomen, has progressively opened or associated with women’s participation in some structures]
-
A.
admittedWomen
chosen
Indicates that an entity allowed or accepted women into a place, group, institution, or event.
-
B.
acceptsStudents
Indicates that an institution or program allows and takes in students as participants or members.
-
C.
admissionGender
Indicates the gender-based criteria or classification applied in the context of admission or entry decisions.
-
D.
hasFemaleRecipients
Indicates that the subject entity has one or more recipients who are female.
-
E.
acceptsMarriageTo
Indicates that one entity formally agrees to enter into a marriage with another entity.
- 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_69d81c5ae7c88190b0dd41bdafeb5999 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0285fb7c8190be4b90bdc0d6fa53 |
completed | April 14, 2026, 9:01 a.m. |
| PD | Predicate disambiguation | batch_69dbc86668e08190ba9135d1c3f38d35 |
completed | April 12, 2026, 4:29 p.m. |
Created at: April 9, 2026, 10:13 p.m.