Triple
T7445562
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hunt-Bovis |
E171868
|
entity |
| Predicate | projectTypeSpecialization |
P6242
|
FINISHED |
| Object | sports stadiums |
—
|
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: sports stadiums | Statement: [Hunt-Bovis, projectTypeSpecialization, sports stadiums]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: projectTypeSpecialization Context triple: [Hunt-Bovis, projectTypeSpecialization, sports stadiums]
-
A.
typicalProjectTypes
Indicates the kinds or categories of projects that are most commonly or characteristically associated with a given entity.
-
B.
typeOfProject
Indicates the specific category or kind of project that an entity is associated with or classified under.
-
C.
creatorSpecialization
Indicates the specific field, discipline, or area of expertise in which a creator primarily works or is specialized.
-
D.
positionSpecialization
Indicates that one position is a more specialized or focused variant of another, broader position.
-
E.
notableProjectType
chosen
Indicates the type or category of a project for which an entity is particularly well-known or notable.
- 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_69c68a65402881908f7869368eb746fb |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f37054388190a6cb4c0db2ca6014 |
completed | March 27, 2026, 9:15 p.m. |
| PD | Predicate disambiguation | batch_69c6f039f7248190bb4183f97b605763 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:14 p.m.