Triple
T3749821
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jonathan Tucker |
E81299
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Jonathan Tucker |
E81299
|
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: Jonathan Tucker | Statement: [Jonathan Tucker, name, Jonathan Tucker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jonathan Tucker Context triple: [Jonathan Tucker, name, Jonathan Tucker]
-
A.
Jonathan Tucker
chosen
Jonathan Tucker is an American actor known for his intense, character-driven roles in film and television, including prominent performances in series like "Kingdom," "Westworld," and "City on a Hill."
-
B.
Richard Gant
Richard Gant is an American character actor known for his roles in film and television, often portraying authoritative or tough-minded figures.
-
C.
Scott Oake
Scott Oake is a Canadian sportscaster best known for his long-running work as a rinkside reporter and host on national hockey broadcasts.
-
D.
Ben Cahoon
Ben Cahoon is a former Canadian Football League slotback widely regarded as one of the most reliable and productive receivers in Montreal Alouettes history.
-
E.
Luke Goss
Luke Goss is an English actor and former drummer best known for his roles in genre films such as "Blade II" and "Hellboy II: The Golden Army."
- 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_69ad8b19b7b08190a6188804e99c53e9 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcb6d0ac4819092c9a41cc60f518d |
completed | March 8, 2026, 7:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b51c6b2a488190a621cc223c673615 |
completed | March 14, 2026, 8:29 a.m. |
Created at: March 8, 2026, 3:35 p.m.