Triple
T3491061
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tuskegee University |
E73730
|
entity |
| Predicate | hasMascot |
P52
|
FINISHED |
| Object | Golden Tiger |
E363473
|
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: Golden Tiger | Statement: [Tuskegee University, hasMascot, Golden Tiger]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Golden Tiger Context triple: [Tuskegee University, hasMascot, Golden Tiger]
-
A.
Golden Tigers
chosen
The Golden Tigers are the athletic teams representing Tuskegee University in intercollegiate sports.
-
B.
Roaring Tiger
Roaring Tiger is the fierce tiger mascot representing Colorado College’s athletic teams and school spirit.
-
C.
Tigery
Tigery is a small commune in the Essonne department of the Île-de-France region in northern France.
-
D.
The Tiger
The Tiger is the costumed feline mascot that represents Princeton University's athletic teams, particularly its football program.
-
E.
Le Tigre
Le Tigre was the fierce political nickname of French statesman Georges Clemenceau, reflecting his combative and determined leadership style, especially during World War I.
- 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_69ad85cca8d4819088494e9f3340fab5 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbbaa720c8190af47b052cc66c225 |
completed | March 8, 2026, 6:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b37e6511b08190b67c353df53599b5 |
completed | March 13, 2026, 3:03 a.m. |
Created at: March 8, 2026, 3:18 p.m.