Triple
T15369589
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Racers |
E367507
|
entity |
| Predicate | mascot |
P52
|
FINISHED |
| Object | Dunker |
E370268
|
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: Dunker | Statement: [Racers, mascot, Dunker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dunker Context triple: [Racers, mascot, Dunker]
-
A.
Dunker
chosen
Dunker is the costumed racehorse mascot that represents Murray State University at its athletic events and campus activities.
-
B.
Dieppe
Dieppe is a historic port city and seaside resort on the English Channel in northern France, known for its pebbled beaches, cliffs, and role in maritime trade and warfare.
-
C.
Dieppe
Dieppe is a rapidly growing city in southeastern New Brunswick, Canada, located next to Moncton and known for its strong Acadian culture and bilingual community.
-
D.
Arromanches-les-Bains
Arromanches-les-Bains is a coastal town in Normandy, France, best known for its role in the D-Day landings and the remains of the Mulberry artificial harbor just offshore.
-
E.
Falaise
Falaise is a town in Normandy, France, known for its strategic role in the Second World War, particularly during the closing of the Falaise Pocket in 1944.
- 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_69d85a1483788190ad93c2748e8af34b |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e4b88a881909f9575c02aed287d |
completed | April 16, 2026, 1:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff0b50703881909ca71c985bc1c7b5 |
completed | May 9, 2026, 10:24 a.m. |
Created at: April 10, 2026, 3:18 a.m.