Triple
T35797754
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sherry Pollex |
E1034882
|
entity |
| Predicate | hasPartnershipWithOrganization |
P27502
|
FINISHED |
| Object | NASCAR-related charities |
—
|
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: NASCAR-related charities | Statement: [Sherry Pollex, hasPartnershipWithOrganization, NASCAR-related charities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPartnershipWithOrganization Context triple: [Sherry Pollex, hasPartnershipWithOrganization, NASCAR-related charities]
-
A.
hasPartnerOrganization
chosen
Indicates that an entity is formally associated or collaborates with another entity as a partner organization.
-
B.
hasPartnershipRole
Indicates that an entity holds a specific role or function within a partnership relationship with another entity.
-
C.
hasPartnershipType
Indicates the specific kind or category of partnership relationship that exists between entities.
-
D.
isNonprofitPartnerOf
Indicates that one entity is a nonprofit organization that collaborates or partners with another entity in a formal or recognized capacity.
-
E.
partnerInOrganizationWith
Indicates that two entities are associated as partners within the same organization or organizational context.
- 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_69f76e169bd081909f16cd8c9ee7870c |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ffe23081408190a121d901dbce1403 |
completed | May 10, 2026, 1:41 a.m. |
| PD | Predicate disambiguation | batch_69ffe18aed348190912a5996b2da728b |
completed | May 10, 2026, 1:38 a.m. |
Created at: May 3, 2026, 4:06 p.m.