Triple
T21447700
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. Orange |
E529120
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | Mr. Pink |
—
|
NE NERFINISHED |
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: Mr. Pink | Statement: [Mr. Orange, associatedWith, Mr. Pink]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mr. Pink Context triple: [Mr. Orange, associatedWith, Mr. Pink]
-
A.
Mr. Pink
chosen
Mr. Pink is the fast-talking, paranoid professional thief played by Steve Buscemi in Quentin Tarantino’s crime film "Reservoir Dogs."
-
B.
Mickey Goldmill
Mickey Goldmill is the gruff, old-school boxing trainer and mentor of Rocky Balboa in the "Rocky" film series.
-
C.
Martin Riggs
Martin Riggs is a reckless yet skilled LAPD detective and former Special Forces soldier known for his suicidal bravado and complex emotional trauma in the Lethal Weapon franchise.
-
D.
Jules Winnfield
Jules Winnfield is a philosophical, sharp-tongued hitman from Quentin Tarantino’s film "Pulp Fiction," known for his memorable monologues and moral transformation.
-
E.
Bill Pink
Bill Pink is an American academic administrator and educator who serves as the president of Ferris State University in Michigan.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c457579481909db68053ed99750c |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9e9d04548819086594c20faa5217d |
completed | April 23, 2026, 9:43 a.m. |
Created at: April 16, 2026, 6:06 p.m.