Triple
T4069009
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boys’ Club |
E86597
|
entity |
| Predicate | genderPolicyHistory |
P26431
|
FINISHED |
| Object | originally focused on serving boys |
—
|
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: originally focused on serving boys | Statement: [Boys’ Club, genderPolicyHistory, originally focused on serving boys]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genderPolicyHistory Context triple: [Boys’ Club, genderPolicyHistory, originally focused on serving boys]
-
A.
hasGenderPolicy
Indicates that an entity has adopted, implemented, or is governed by a specific policy related to gender issues or gender equality.
-
B.
historicalLanguagePolicy
Indicates a relationship where an authority’s past rules or practices governed the use, status, or regulation of a language within a society or institution.
-
C.
hasGenderHistory
Indicates that an entity has undergone or experienced a change or transition in gender over time.
-
D.
demographicPolicy
Indicates a relationship where an authority or organization establishes or applies rules and measures intended to influence the size, structure, or composition of a population.
-
E.
hasPolicyHistory
chosen
Indicates that an entity is associated with a record or sequence of past policies that have applied to it over time.
- 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_69aed93ebe448190a1f1686e28740ac9 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefbf8f33c8190a6afca1830f35485 |
completed | March 9, 2026, 4:57 p.m. |
| PD | Predicate disambiguation | batch_69aef9061d2481908307cafc9e9b32c0 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:38 p.m.