Triple
T5832413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Memphis |
E129381
|
entity |
| Predicate | mascot |
P52
|
FINISHED |
| Object | Pouncer |
E89352
|
NE 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: Pouncer | Statement: [University of Memphis, mascot, Pouncer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pouncer Context triple: [University of Memphis, mascot, Pouncer]
-
A.
Pouncer
chosen
Pouncer is the costumed tiger mascot who represents the University of Memphis Tigers at athletic events and school functions.
-
B.
Poons
Poons is a surname most notably associated with Larry Poons, an American abstract painter known for his innovative use of color and optical effects.
-
C.
Pookie
Pookie is a tragic, crack-addicted informant character from the 1991 crime film "New Jack City," portrayed by Chris Rock.
-
D.
Pounce
Pounce is the costumed panther mascot representing Georgia State University at its athletic events and campus activities.
-
E.
Poosh
Poosh is Kourtney Kardashian’s lifestyle and wellness brand and content platform, featuring advice, products, and curated recommendations on beauty, health, and living.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c0084af79c81908af128ccc29983d0 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0346c331c8190bac050d425961485 |
completed | March 22, 2026, 6:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0a19010008190af5600a035246c1a |
completed | March 23, 2026, 2:12 a.m. |
Created at: March 22, 2026, 3:54 p.m.