Triple
T4360594
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Fire Service (United Kingdom) |
E98650
|
entity |
| Predicate | includedWomen |
P12173
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [National Fire Service (United Kingdom), includedWomen, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includedWomen Context triple: [National Fire Service (United Kingdom), includedWomen, yes]
-
A.
includesWomenStructure
Indicates that the referenced entity contains or incorporates a structural component specifically designed for or involving women.
-
B.
womenStatus
Indicates the social, legal, economic, or cultural position or condition assigned to women within a given context or system.
-
C.
admittedWomen
chosen
Indicates that an entity allowed or accepted women into a place, group, institution, or event.
-
D.
hadWomenOrganization
Indicates that an entity was associated with or involved in an organization focused on women or women’s issues.
-
E.
genderEquality
Indicates that the relationship or action promotes, reflects, or ensures equal rights, opportunities, and treatment for all genders without discrimination.
- 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_69b3454c772081908e20173e379e8ebe |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b351e3220881909dc9d02ab024abf5 |
completed | March 12, 2026, 11:53 p.m. |
| PD | Predicate disambiguation | batch_69b34f53e3cc8190bf5d4dbe2413bf65 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:16 p.m.