Triple
T9873385
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tausha Kutcher |
E240013
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Kutcher |
E236181
|
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: Kutcher | Statement: [Tausha Kutcher, familyName, Kutcher]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kutcher Context triple: [Tausha Kutcher, familyName, Kutcher]
-
A.
Kutcher
chosen
Kutcher is the surname of American actor, producer, and entrepreneur Ashton Kutcher, known for his roles in television and film as well as his tech investments.
-
B.
Ken Kershaw
Ken Kershaw is a notable individual distinguished enough to be recognized as a prominent bearer of the surname Kershaw.
-
C.
Charlie Kelmeckis
Charlie Kelmeckis is the introspective teenage protagonist and narrator of Stephen Chbosky’s coming-of-age novel and film "The Perks of Being a Wallflower."
-
D.
Keefer
Keefer was a distinguished racing greyhound renowned for its achievements on the track, earning induction into the Greyhound Hall of Fame.
-
E.
Billy Kearns
Billy Kearns was an American character actor known for his supporting roles in mid-20th-century film and television.
- 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_69ca84e8a0788190b9061811d50fd554 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb3f754008190abe3fe034b42908e |
completed | April 2, 2026, 12:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1e46f18148190a36af7e7d7487205 |
completed | April 5, 2026, 4:26 a.m. |
Created at: March 30, 2026, 8:37 p.m.