Triple
T35120019
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sheiks |
E1014140
|
entity |
| Predicate | mascotOrNicknameFor |
P139554
|
FINISHED |
| Object | Hollywood High School sports teams |
—
|
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: Hollywood High School sports teams | Statement: [Sheiks, mascotOrNicknameFor, Hollywood High School sports teams]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mascotOrNicknameFor Context triple: [Sheiks, mascotOrNicknameFor, Hollywood High School sports teams]
-
A.
mascotName
Indicates the name assigned to a mascot that represents an entity.
-
B.
mascotCollectiveName
chosen
Indicates that a mascot is associated with and represents a particular collective group, organization, or team name.
-
C.
isMascotCounterpartOf
Indicates that one entity serves as the mascot equivalent or counterpart of another entity, typically representing the same thing in a mascot form.
-
D.
mascotSlogan
Indicates that a particular slogan is associated with or used by a specific mascot.
-
E.
hasMascot
Indicates that an entity is represented or symbolized by a particular mascot.
- 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_69f76dd8b6948190aaa32b081816bd94 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78ce78b508190955848e133398dc8 |
completed | May 3, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69f78b8f4cc08190b49fccd798cb25d7 |
completed | May 3, 2026, 5:53 p.m. |
Created at: May 3, 2026, 4:01 p.m.