Triple
T11886470
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stokely Mitchell |
E282794
|
entity |
| Predicate | hasLoveInterest |
P7325
|
FINISHED |
| Object | Stan Rosado |
E259265
|
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: Stan Rosado | Statement: [Stokely Mitchell, hasLoveInterest, Stan Rosado]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stan Rosado Context triple: [Stokely Mitchell, hasLoveInterest, Stan Rosado]
-
A.
Stan Rosado
chosen
Stan Rosado is a character from the 1998 sci-fi horror film "The Faculty," which follows a group of high school students who discover their teachers are being taken over by alien parasites.
-
B.
Don Saleski
Don Saleski is a former NHL right winger best known for his gritty, physical play with the Philadelphia Flyers during their 1970s "Broad Street Bullies" era.
-
C.
Lance Leipold
Lance Leipold is an American college football coach known for successfully rebuilding programs, most notably turning around the University of Kansas Jayhawks football team after winning multiple Division III national titles at Wisconsin–Whitewater.
-
D.
Dennis Sallas
Dennis Sallas is an actor known for appearing in the film "Shadows."
-
E.
Beat Suter
Beat Suter is a Swiss game designer, media artist, and scholar known for his work in digital literature, game studies, and experimental media.
- 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_69d6ab2a90b08190a4e818821cc93e6d |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8d3a13370819086386fecb99e4f0b |
completed | April 10, 2026, 10:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f43fd661f481909b1f7609540e42d7 |
completed | May 1, 2026, 5:53 a.m. |
Created at: April 8, 2026, 9:44 p.m.