Triple
T10280888
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rupert Sanders |
E241096
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Rupert Sanders |
E241096
|
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 Sanders | Statement: [Rupert Sanders, name, Rupert Sanders]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rupert Sanders Context triple: [Rupert Sanders, name, Rupert Sanders]
-
A.
Rupert Sanders
chosen
Rupert Sanders is a British film director best known for making his feature debut with the dark fantasy film "Snow White and the Huntsman."
-
B.
Gareth Edwards
Gareth Edwards is a British filmmaker known for directing large-scale science fiction and monster films such as "Monsters," "Godzilla" (2014), and "Rogue One: A Star Wars Story."
-
C.
Gareth Edwards
Gareth Edwards is a Welsh former rugby union scrum-half widely regarded as one of the greatest rugby players of all time.
-
D.
Travis Knight
Travis Knight is an American animator, film director, and CEO of the stop-motion animation studio Laika, known for directing films such as "Kubo and the Two Strings."
-
E.
Wes Ball
Wes Ball is an American film director best known for helming the Maze Runner science-fiction film series.
- 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_69d381a94c1881908fc38fc263d9b9c2 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2a0c90c8190ad6ee479a32e5a95 |
completed | April 7, 2026, 9:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6f82f16688190b1c6b80e424bd552 |
completed | April 9, 2026, 12:51 a.m. |
Created at: April 6, 2026, 11:38 a.m.