Triple
T20164304
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sheen Estevez |
E491788
|
entity |
| Predicate | fullName |
P16
|
FINISHED |
| Object | Sheen Juarrera Estevez |
—
|
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: Sheen Juarrera Estevez | Statement: [Sheen Estevez, fullName, Sheen Juarrera Estevez]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sheen Juarrera Estevez Context triple: [Sheen Estevez, fullName, Sheen Juarrera Estevez]
-
A.
Sheen Estevez
chosen
Sheen Estevez is a hyperactive, dim-witted, and Ultralord-obsessed boy from the animated series "The Adventures of Jimmy Neutron: Boy Genius."
-
B.
Sheen
Sheen is a historic area in southwest London, England, known for its royal connections and the former site of Sheen Palace.
-
C.
Sheen
Sheen is a central protagonist in Piers Anthony's "Apprentice Adept" science fantasy series, known for navigating the dual worlds of magic and technology.
-
D.
Eriq La Salle
Eriq La Salle is an American actor, director, and producer best known for his role as Dr. Peter Benton on the television series "ER."
-
E.
Lee Tergesen
Lee Tergesen is an American actor best known for his roles in the HBO series "Oz," the film "Wayne's World," and numerous television dramas and miniseries.
- 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_69da6266c6888190bc1a3ecf24814d34 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e6684376408190a68890ab48fa5424 |
completed | April 20, 2026, 5:54 p.m. |
Created at: April 11, 2026, 11:35 p.m.