Triple
T18081257
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wes Studi |
E432693
|
entity |
| Predicate | hasChild |
P369
|
FINISHED |
| Object |
Daniel Studi
Daniel Studi is the son of acclaimed Native American actor Wes Studi.
|
E1305762
|
NE FINISHED |
How this triple was built (4 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: Daniel Studi | Statement: [Wes Studi, hasChild, Daniel Studi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daniel Studi Context triple: [Wes Studi, hasChild, Daniel Studi]
-
A.
Jack Studnicka
Jack Studnicka is a Canadian professional ice hockey forward who has played in the NHL after developing through junior leagues in Ontario.
-
B.
Daniel Silna
Daniel Silna is an American businessman best known for co-owning the former ABA team Spirits of St. Louis and securing one of the most lucrative television revenue deals in sports history when the league merged with the NBA.
-
C.
Daniel Hartmann
Daniel Hartmann is a German local politician who serves as the mayor of the town of Höxter in North Rhine-Westphalia.
-
D.
David Kaemmer
David Kaemmer is a video game designer and programmer best known as the co-founder of Papyrus Design Group and iRacing, where he created influential racing simulation games.
-
E.
Daniel Bekerman
Daniel Bekerman is a Canadian film producer known for working on independent and genre films, including the horror-comedy thriller "Come to Daddy."
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Daniel Studi Triple: [Wes Studi, hasChild, Daniel Studi]
Generated description
Daniel Studi is the son of acclaimed Native American actor Wes Studi.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Daniel Studi Target entity description: Daniel Studi is the son of acclaimed Native American actor Wes Studi.
-
A.
Jack Studnicka
Jack Studnicka is a Canadian professional ice hockey forward who has played in the NHL after developing through junior leagues in Ontario.
-
B.
Daniel Silna
Daniel Silna is an American businessman best known for co-owning the former ABA team Spirits of St. Louis and securing one of the most lucrative television revenue deals in sports history when the league merged with the NBA.
-
C.
Daniel Hartmann
Daniel Hartmann is a German local politician who serves as the mayor of the town of Höxter in North Rhine-Westphalia.
-
D.
David Kaemmer
David Kaemmer is a video game designer and programmer best known as the co-founder of Papyrus Design Group and iRacing, where he created influential racing simulation games.
-
E.
Daniel Bekerman
Daniel Bekerman is a Canadian film producer known for working on independent and genre films, including the horror-comedy thriller "Come to Daddy."
- F. None of above. chosen
Provenance (5 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_69d8b907d05c819083cc3bd6021089e6 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4d9fa080081909e1a05e98185a026 |
completed | April 19, 2026, 1:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a035d8d4ab881909b2ebe0b933e3b97 |
completed | May 12, 2026, 5:04 p.m. |
| NEDg | Description generation | batch_6a0360cc5d648190bd7d7d756f662046 |
completed | May 12, 2026, 5:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a03616317548190a09b0df1c9d6d303 |
completed | May 12, 2026, 5:20 p.m. |
Created at: April 10, 2026, 10:27 a.m.