Triple
T15566398
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Exorcist (TV series) |
E371125
|
entity |
| Predicate | developer |
P73
|
FINISHED |
| Object | Jeremy Slater |
E322030
|
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: Jeremy Slater | Statement: [The Exorcist (TV series), developer, Jeremy Slater]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jeremy Slater Context triple: [The Exorcist (TV series), developer, Jeremy Slater]
-
A.
Jeremy Slater
chosen
Jeremy Slater is an American screenwriter and producer best known for his work on genre projects such as the 2015 Fantastic Four film and the TV series The Exorcist and Moon Knight.
-
B.
Matthew Slipper
Matthew Slipper is a software engineer and Ethereum contributor known for co-authoring the EIP-1559 fee market improvement proposal.
-
C.
Dan Slater
Dan Slater is the protagonist of the thriller novel "The Double Man," around whom the story’s central intrigue and conflict revolve.
-
D.
Ian Slater
Ian Slater is a film editor best known for his work on major feature films, including entries in the Twilight Saga.
-
E.
Adrian Sutton
Adrian Sutton is a British composer best known for his theatrical scores, particularly his work with the National Theatre in London.
- 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_69d85cc6cf40819091f4a5facee1ebe6 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04ddd753c8190b51eaef433258081 |
completed | April 16, 2026, 2:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff456a3b08819092f9f517bbef5577 |
completed | May 9, 2026, 2:32 p.m. |
Created at: April 10, 2026, 4:10 a.m.