Triple
T12992183
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Apted |
E321931
|
entity |
| Predicate | directed |
P7373
|
FINISHED |
| Object | Nell |
E959016
|
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: Nell | Statement: [Michael Apted, directed, Nell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nell Context triple: [Michael Apted, directed, Nell]
-
A.
Nell
Nell is a feminine given name, often used as a diminutive of names like Eleanor or Helen.
-
B.
Nell
chosen
Nell is a 1994 American drama film starring Jodie Foster as a reclusive young woman raised in isolation, known for its exploration of language, communication, and societal integration.
-
C.
Nellie
Nellie is the familiar nickname of Nellie Connally, the former First Lady of Texas who was riding in the car with President John F. Kennedy during his assassination in 1963.
-
D.
Nellie
Nellie is the given first name of the American actress, singer, and television host Polly Bergen.
-
E.
Nellie
Nellie is a central character in the British period drama series "Lark Rise to Candleford," which portrays life in a rural English community in the late 19th century.
- 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_69d8076479b8819090afce3591939cdf |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97e7765788190a9503ef055bc30ca |
completed | April 10, 2026, 10:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6c0fca5e4819086b010fdd1813419 |
completed | May 3, 2026, 3:29 a.m. |
Created at: April 9, 2026, 8:44 p.m.