Triple
T28626133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Axemen |
E724527
|
entity |
| Predicate | usesMascotType |
P84914
|
FINISHED |
| Object | axeman / lumberjack-themed identity |
—
|
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: axeman / lumberjack-themed identity | Statement: [Axemen, usesMascotType, axeman / lumberjack-themed identity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesMascotType Context triple: [Axemen, usesMascotType, axeman / lumberjack-themed identity]
-
A.
hasMascotIdentity
Indicates that an entity serves as or possesses the role/identity of a mascot for another entity.
-
B.
isMascot
Indicates that one entity serves as the mascot or symbolic representative for another entity, such as an organization, team, or event.
-
C.
usesLiveMascot
Indicates that an entity employs a real, living mascot (such as an animal or person) to represent or promote itself.
-
D.
hasMascotFeature
chosen
Indicates that an entity possesses a specific characteristic, attribute, or element related to a mascot.
-
E.
usesMascotNameDerivedFrom
Indicates that one entity adopts and uses a mascot whose name is derived from, based on, or inspired by another entity.
- 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_69f01d822ac08190932de59ec2268ed2 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69f6b903538481909cffcb6cc1cc0e70 |
completed | May 3, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69f6b626120c819097c9ad04487570d7 |
completed | May 3, 2026, 2:42 a.m. |
Created at: April 28, 2026, 4:36 a.m.