Triple
T16811182
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | I Am Cait |
E408613
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object | Gil Goldschein |
—
|
NE NERFINISHED |
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: Gil Goldschein | Statement: [I Am Cait, executiveProducer, Gil Goldschein]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gil Goldschein Context triple: [I Am Cait, executiveProducer, Gil Goldschein]
-
A.
Gil Goldschein
chosen
Gil Goldschein is a television producer and media executive best known for his work on reality TV series, including projects in the Kardashian franchise.
-
B.
Nahum Gelber
Nahum Gelber was a Canadian lawyer, philanthropist, and community leader known for his significant contributions to legal education and Jewish cultural and charitable institutions.
-
C.
Mitch Goldhar
Mitch Goldhar is a Canadian billionaire real estate developer and businessman best known for owning the Israeli football club Maccabi Tel Aviv F.C.
-
D.
Bernard Goldstein
Bernard Goldstein is a notable individual whose achievements or prominence have made the surname Goldstein particularly recognized.
-
E.
Leo Salkin
Leo Salkin was an American animator, writer, and storyboard artist known for his work on mid-20th-century animated films and shorts.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d88393905081908d00a86b99996ac8 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b2d0793c81909d938ac174a6e63a |
completed | April 18, 2026, 4:35 p.m. |
Created at: April 10, 2026, 5:23 a.m.