Triple
T5711841
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jonathan Gold |
E125927
|
entity |
| Predicate | fullName |
P16
|
FINISHED |
| Object | Jonathan Gold |
E125927
|
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 Gold | Statement: [Jonathan Gold, fullName, Jonathan Gold]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jonathan Gold Context triple: [Jonathan Gold, fullName, Jonathan Gold]
-
A.
Jonathan Gold
chosen
Jonathan Gold was an influential American food critic renowned for his vivid, democratizing explorations of Los Angeles’s diverse culinary landscape.
-
B.
Josh Goldstein
Josh Goldstein is a screenwriter best known for co-writing the story for Disney’s adventure film "Jungle Cruise."
-
C.
Daniel Patterson
Daniel Patterson was the first husband of Mary Baker Eddy, the founder of Christian Science.
-
D.
Dan Trachtenberg
Dan Trachtenberg is an American filmmaker best known for directing the thriller "10 Cloverfield Lane" and the "Predator" prequel "Prey."
-
E.
Mark Goldblatt
Mark Goldblatt is an American film editor best known for his work on high-profile action movies such as The Terminator, Predator 2, and Rambo: First Blood Part II.
- 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_69c0082d6fe48190b777fb383769e5c8 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c024b386a08190bd2738d93861edc2 |
completed | March 22, 2026, 5:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c05a72181081909209a38c3ff7460b |
completed | March 22, 2026, 9:09 p.m. |
Created at: March 22, 2026, 3:46 p.m.