Triple
T13796520
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Mercenary |
E331530
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object | Curly |
E463813
|
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: Curly | Statement: [The Mercenary, featuresCharacter, Curly]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Curly Context triple: [The Mercenary, featuresCharacter, Curly]
-
A.
Curly Neal
Curly Neal was a legendary American basketball showman best known as the bald, ball-handling wizard and longtime star of the Harlem Globetrotters.
-
B.
J. Fred Muggs
J. Fred Muggs is a chimpanzee who became a popular television personality and cultural icon in the 1950s as the mascot of NBC’s Today show.
-
C.
John Curly
John Curly is a technology executive best known as a co-founder of EMC Corporation, a major data storage and information management company.
-
D.
Curly McLain
Curly McLain is the charming cowboy protagonist of the classic Rodgers and Hammerstein musical "Oklahoma!"
-
E.
Curly Howard
chosen
Curly Howard was an American comedian best known as the most popular and zany member of the slapstick comedy team The Three Stooges.
- 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_69d81c58feb08190a77bca8bf7d6d20f |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de025be1f08190aac525d72d7dc0c3 |
completed | April 14, 2026, 9:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b08508688190b7e8c33e6b65e25d |
completed | May 3, 2026, 8:31 p.m. |
Created at: April 9, 2026, 10:11 p.m.