Triple
T18022319
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Annie Ross |
E431154
|
entity |
| Predicate | sibling |
P363
|
FINISHED |
| Object | Jimmy Logan |
—
|
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: Jimmy Logan | Statement: [Annie Ross, sibling, Jimmy Logan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jimmy Logan Context triple: [Annie Ross, sibling, Jimmy Logan]
-
A.
Jimmy Logan
chosen
Jimmy Logan was a Scottish comedian and actor known for his work in film, television, and theatre, particularly in British comedy.
-
B.
Jimmy Logan
Jimmy Logan is the down-on-his-luck West Virginian construction worker who masterminds the NASCAR heist at the center of the film "Logan Lucky."
-
C.
Tom Logan
Tom Logan is the charismatic defense attorney portrayed by Robert Redford in the 1986 legal comedy film "Legal Eagles."
-
D.
Tom Logan
Tom Logan is a fictional rustler and gang leader portrayed by Jack Nicholson in the 1976 Western film "The Missouri Breaks."
-
E.
Don Logan
Don Logan is a volatile and menacing criminal character from the British film "Sexy Beast," best known for Ben Kingsley’s intense, Oscar-nominated performance.
- 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_69d8b9050fb48190890155145deb0a66 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4b9c3a2c48190bbe4a0581466cd2f |
completed | April 19, 2026, 11:17 a.m. |
Created at: April 10, 2026, 10:24 a.m.