Triple
T9465024
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clinton Sundberg |
E228248
|
entity |
| Predicate | nameInNativeLanguage |
P1435
|
FINISHED |
| Object | Clinton Sundberg |
E228248
|
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: Clinton Sundberg | Statement: [Clinton Sundberg, nameInNativeLanguage, Clinton Sundberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Clinton Sundberg Context triple: [Clinton Sundberg, nameInNativeLanguage, Clinton Sundberg]
-
A.
Clinton Sundberg
chosen
Clinton Sundberg was an American character actor known for his supporting roles in mid-20th-century Hollywood films and stage productions.
-
B.
Darin Erstad
Darin Erstad is a former Major League Baseball outfielder and first baseman best known for his key role with the Anaheim Angels, including their championship run in the early 2000s.
-
C.
Rich Sutter
Rich Sutter is a former Canadian professional ice hockey winger who played in the NHL and is part of the well-known Sutter hockey family.
-
D.
Mike Seaver
Mike Seaver is the mischievous yet good-hearted teenage son and central figure in the 1980s American sitcom "Growing Pains."
-
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_69ca846fee388190a6ec273fd644b88b |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7fdad3c4819083b06f1b45acc85a |
completed | April 1, 2026, 8:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d122b1440c81909de61d4e72eb93f4 |
completed | April 4, 2026, 2:39 p.m. |
Created at: March 30, 2026, 7:53 p.m.