Triple
T12087595
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Critters 4 |
E287847
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Rupert Harvey |
E976405
|
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: Rupert Harvey | Statement: [Critters 4, producer, Rupert Harvey]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rupert Harvey Context triple: [Critters 4, producer, Rupert Harvey]
-
A.
Rupert Harvey
chosen
Rupert Harvey is a film producer and director best known for his work on the Critters horror-comedy franchise.
-
B.
Rupert Baxter
Rupert Baxter is a recurring character in P. G. Wodehouse’s Blandings Castle stories, known as the hyper-efficient, suspicious former secretary whose attempts to impose order often lead to comic chaos.
-
C.
Rupert Preston
Rupert Preston is a British film producer known for his work on independent and genre films, including the crime drama "Bronson."
-
D.
Rupert Thompson
Rupert Thompson was a benefactor whose contributions to Dartmouth College led to the university’s ice hockey arena being named in his honor.
-
E.
Rupert Young
Rupert Young is a British actor best known for his television and stage work, including roles in series like "Merlin" and various West End productions.
- 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_69d6ab4964708190850585628b287b0c |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d91514c78c8190bc1cd569e524e8b4 |
completed | April 10, 2026, 3:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f62a7e1ab481909c25ba3dd3fff9b3 |
completed | May 2, 2026, 4:46 p.m. |
Created at: April 8, 2026, 9:48 p.m.