Triple
T33184855
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Calvada Productions |
E849437
|
entity |
| Predicate | associatedShowProducer |
P206376
|
FINISHED |
| Object | Sheldon Leonard |
E99778
|
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: Sheldon Leonard | Statement: [Calvada Productions, associatedShowProducer, Sheldon Leonard]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedShowProducer Context triple: [Calvada Productions, associatedShowProducer, Sheldon Leonard]
-
A.
associatedProduction
Indicates that there is a related or connected production (such as a work, performance, or manufacturing process) linked to the subject entity.
-
B.
executiveProducerAssociated
Indicates that an entity serves as or is associated with the executive producer role for another entity, such as a film, show, or project.
-
C.
associatedWithShowCreators
Indicates a relationship where an entity is linked or connected to the creators of a particular show.
-
D.
associatedShow
Indicates a relationship where one entity is linked or connected to a particular show (e.g., as its subject, source, or related program).
-
E.
associatedWithProducerOfFilm
Indicates that one entity has an association or connection with the producer of a particular film.
- F. None of above. chosen
Provenance (5 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_69f3495e0f108190a6a7006f79f9c2c3 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3525cd97a48190928fbe734cde7fab |
completed | June 19, 2026, 11:19 a.m. |
| PD | Predicate disambiguation | batch_6a0379f338b881908e5593e45d764f4d |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c7fb9f88190b384b1b68200aef0 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 1, 2026, 1:29 a.m.