Triple
T5699642
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jon Tenney |
E125626
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Jon Tenney |
E125626
|
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: Jon Tenney | Statement: [Jon Tenney, name, Jon Tenney]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jon Tenney Context triple: [Jon Tenney, name, Jon Tenney]
-
A.
Jon Tenney
chosen
Jon Tenney is an American actor best known for his role as FBI Special Agent Fritz Howard on the television crime drama series "The Closer."
-
B.
Allen Ludden
Allen Ludden was an American television personality and game show host best known for hosting the quiz show "Password."
-
C.
John Bishop
John Bishop is an English stand-up comedian, actor, and television presenter known for his energetic storytelling style and appearances on British panel shows and dramas.
-
D.
Mitch Besser
Mitch Besser is an American gynecologist and public health specialist known for his work in HIV/AIDS prevention and as the husband of Scottish singer-songwriter Annie Lennox.
-
E.
Bill Murphy
Bill Murphy is a film editor known for his work on the Australian drama film "Romper Stomper."
- 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_69c0082c96988190b3a6a201edce472a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0241030408190be774a5d2ca6e999 |
completed | March 22, 2026, 5:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c05a5c89b88190a397c6b1dcb9c3e8 |
completed | March 22, 2026, 9:08 p.m. |
Created at: March 22, 2026, 3:45 p.m.