Triple
T20006823
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Behind Her Eyes |
E494480
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object | Louise Barnsley |
—
|
NE NERFINISHED |
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: Louise Barnsley | Statement: [Behind Her Eyes, mainCharacter, Louise Barnsley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Louise Barnsley Context triple: [Behind Her Eyes, mainCharacter, Louise Barnsley]
-
A.
Louise Barnsley
chosen
Louise Barnsley is a central character in the psychological thriller series "Behind Her Eyes," known for becoming entangled in a dangerous love triangle and a web of dark secrets.
-
B.
Louise Nicholl
Louise Nicholl is a notable individual recognized for bearing the surname Nicholl.
-
C.
Sarah Barnard
Sarah Barnard is a relatively obscure individual for whom no widely known public information or distinguishing background is readily available.
-
D.
Sarah Barnard
Sarah Barnard was the wife of renowned English scientist Michael Faraday, providing personal support throughout his career in 19th-century London.
-
E.
Anne Barnard
Anne Barnard is a journalist and foreign correspondent known for her reporting on conflict zones and Middle Eastern affairs, particularly for The New York Times.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da626b2d748190886981ea90c8b2ea |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e661a648a88190853ee741edcf6ca2 |
completed | April 20, 2026, 5:25 p.m. |
Created at: April 11, 2026, 3:33 p.m.