Triple
T27102152
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barnett College |
E686468
|
entity |
| Predicate | hasMascotStatus |
P40901
|
FINISHED |
| Object | mascot not specified in canon |
—
|
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: mascot not specified in canon | Statement: [Barnett College, hasMascotStatus, mascot not specified in canon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMascotStatus Context triple: [Barnett College, hasMascotStatus, mascot not specified in canon]
-
A.
hasMascot
Indicates that an entity is represented or symbolized by a particular mascot.
-
B.
hasMascotIdentity
Indicates that an entity serves as or possesses the role/identity of a mascot for another entity.
-
C.
mascotStatus
chosen
Indicates the role or designation of an entity as a mascot, such as whether and how it serves as a symbolic representative.
-
D.
hasMascotFeature
Indicates that an entity possesses a specific characteristic, attribute, or element related to a mascot.
-
E.
mascotPresent
Indicates that a mascot is present or participating in the specified context or event.
- 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_69ef1489f8b481908e24a1985982bd26 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69fdbaa226708190b8ed96e93aad38de |
completed | May 8, 2026, 10:27 a.m. |
| PD | Predicate disambiguation | batch_69fdb58b07e48190837e00966de050d4 |
completed | May 8, 2026, 10:06 a.m. |
Created at: April 27, 2026, 8:48 a.m.