Triple
T2532973
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Florida State Seminoles football |
E56202
|
entity |
| Predicate | recruitingReputation |
P39426
|
FINISHED |
| Object | consistently strong |
—
|
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: consistently strong | Statement: [Florida State Seminoles football, recruitingReputation, consistently strong]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recruitingReputation Context triple: [Florida State Seminoles football, recruitingReputation, consistently strong]
-
A.
recruitingProfile
Indicates that an entity serves as or is associated with a recruiting profile used for hiring or talent acquisition activities.
-
B.
reputationBuiltFor
Indicates that one entity has established or developed a reputation specifically for or in relation to another entity.
-
C.
recruitmentFrom
Indicates that one entity recruits or sources members, employees, or participants from another entity.
-
D.
associatedWithReputation
Indicates a relationship where an entity is linked to, influenced by, or characterized in terms of another entity’s reputation or perceived standing.
-
E.
recruitedAs
Indicates that one entity has been brought into a role, position, or organization by another through a recruitment process.
- F. None of above. chosen
Provenance (4 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_69ab4a49b6508190bc467fbef4bac334 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd27afe7c8190984e10d3f3d5586b |
completed | March 7, 2026, 7:23 a.m. |
| PD | Predicate disambiguation | batch_69abd0c2e34c8190a914d5c2afba147c |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd18e72a88190bdcf12b326d42fad |
completed | March 7, 2026, 7:19 a.m. |
Created at: March 6, 2026, 9:47 p.m.