Triple
T2269938
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saul Zaentz |
E50632
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | Fantasy Records |
E211003
|
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: Fantasy Records | Statement: [Saul Zaentz, employer, Fantasy Records]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fantasy Records Context triple: [Saul Zaentz, employer, Fantasy Records]
-
A.
Fantasy Records
chosen
Fantasy Records is an American independent record label best known for its influential jazz catalog, including releases by artists like Dave Brubeck and Vince Guaraldi.
-
B.
Fontana Records
Fontana Records is a British record label known for releasing a wide range of pop, rock, and jazz recordings, particularly during the 1960s and 1970s.
-
C.
EmArcy Records
EmArcy Records is a jazz-focused record label, originally a Mercury Records imprint, known for releasing influential recordings by artists such as Erroll Garner.
-
D.
Streamline Records
Streamline Records is a record label associated with major pop acts, notably helping launch the early career of American singer-songwriter Lady Gaga.
-
E.
Rowdy Records
Rowdy Records is a record label known for working with R&B artists such as Monica in the 1990s.
- 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_69a88b05910c8190a9a2b1ff230c85f9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc1be90708190b8878c393dd2a42d |
completed | March 7, 2026, 6:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae71d97a108190a26ffd20fac91a7e |
completed | March 9, 2026, 7:08 a.m. |
Created at: March 4, 2026, 7:48 p.m.