Triple
T6320596
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fat Sam |
E141726
|
entity |
| Predicate | enemyOf |
P437
|
FINISHED |
| Object | Dandy Dan |
E134603
|
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: Dandy Dan | Statement: [Fat Sam, enemyOf, Dandy Dan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dandy Dan Context triple: [Fat Sam, enemyOf, Dandy Dan]
-
A.
Dandy Dan
chosen
Dandy Dan is the sharply dressed, ruthless mob boss antagonist in the 1976 musical gangster film "Bugsy Malone."
-
B.
Dandy Don
Dandy Don was the popular nickname of Don Meredith, a star Dallas Cowboys quarterback and pioneering color commentator on Monday Night Football.
-
C.
Handsome Dan
Handsome Dan is the live bulldog mascot and enduring symbol of Yale University's athletic teams and school spirit.
-
D.
Dum Dum Dugan
Dum Dum Dugan is a gruff, mustachioed World War II-era soldier and close ally of Nick Fury in Marvel Comics, renowned for his combat skills and leadership within elite military units.
-
E.
Squirrely Dan
Squirrely Dan is a lovable, soft-spoken, and philosophically inclined hick from the Canadian comedy series "Letterkenny," known for his quirky manner of speaking and loyal friendship.
- 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_69c008d13b8c8190be47d896eb735605 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c064c61f008190b316b9ff1023b057 |
completed | March 22, 2026, 9:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c5e48a8c5c819099f21fdff1ce43f3 |
completed | March 27, 2026, 1:59 a.m. |
Created at: March 22, 2026, 4:29 p.m.