Triple
T34532519
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mike I |
E886576
|
entity |
| Predicate | universityMascotSeries |
P44175
|
FINISHED |
| Object | Mike the Tiger |
—
|
NE NERFINISHED |
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: Mike the Tiger | Statement: [Mike I, universityMascotSeries, Mike the Tiger]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: universityMascotSeries Context triple: [Mike I, universityMascotSeries, Mike the Tiger]
-
A.
universityMascot
chosen
Indicates that one entity serves as the official mascot representing a particular university.
-
B.
mascotTheme
Indicates that an entity serves as the representative mascot associated with a particular theme, concept, or style.
-
C.
mascotOfHighSchool
Indicates that one entity serves as the official mascot representing a particular high school.
-
D.
mascotSlogan
Indicates that a particular slogan is associated with or used by a specific mascot.
-
E.
isMascotCounterpartOf
Indicates that one entity serves as the mascot equivalent or counterpart of another entity, typically representing the same thing in a mascot form.
- 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_69f349cd7c148190aa99192b126d1527 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f727bde8f88190ad746ca515134ca1 |
completed | May 3, 2026, 10:47 a.m. |
| PD | Predicate disambiguation | batch_69f72739c30c81908642eef3feb3afcf |
completed | May 3, 2026, 10:45 a.m. |
Created at: May 1, 2026, 2:02 a.m.