Triple
T25651222
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ohio Women's Rights Convention, Akron, Ohio |
E643102
|
entity |
| Predicate | raceFocus |
P110875
|
FINISHED |
| Object | African American women |
—
|
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: African American women | Statement: [Ohio Women's Rights Convention, Akron, Ohio, raceFocus, African American women]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: raceFocus Context triple: [Ohio Women's Rights Convention, Akron, Ohio, raceFocus, African American women]
-
A.
raceRegion
Indicates that an instance of a race takes place within, or is associated with, a specific geographic region.
-
B.
raceRole
Indicates the specific role, position, or function an entity holds within a race or racing event.
-
C.
relatedRace
Indicates that there is a connection or association between two races, such as similarity, relevance, or contextual linkage.
-
D.
notableRaceFocus
chosen
Indicates that the subject is particularly known for, associated with, or focused on a specific race or racial group.
-
E.
raceContext
Indicates the situational or environmental circumstances under which a race or competitive event takes place.
- 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_69e77e7d8a848190a98d0162325fd780 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f5faa88aec819082bca8efba424a91 |
completed | May 2, 2026, 1:22 p.m. |
| PD | Predicate disambiguation | batch_69f4807f8680819098a524158d049c63 |
completed | May 1, 2026, 10:29 a.m. |
Created at: April 21, 2026, 6:23 p.m.