Triple
T8415509
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Legend (1985 film) |
E198720
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Mia Sara |
E535836
|
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: Mia Sara | Statement: [Legend (1985 film), starring, Mia Sara]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mia Sara Context triple: [Legend (1985 film), starring, Mia Sara]
-
A.
Mia Sara
chosen
Mia Sara is an American actress best known for her role as Sloane Peterson in the 1986 teen comedy film "Ferris Bueller's Day Off."
-
B.
Mia Morgan
Mia Morgan is a central character in the romantic comedy-drama film "The Best Man," around whom much of the story’s interpersonal conflict and emotional tension revolves.
-
C.
Sarra Kemp
Sarra Kemp is the wife of British track cycling champion and multiple Olympic gold medallist Sir Chris Hoy.
-
D.
Sara Barone
Sara Barone is a composer best known for her work on the nature documentary series Planet Earth III.
-
E.
Sara
Sara was the internal codename used by Apple for its Apple III personal computer during development.
- 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_69ca831201b481909e137936ef99ff11 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cb83e443a08190983d9a0a61e0f781 |
completed | March 31, 2026, 8:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce0333a3488190ba30d03b1d7bacb1 |
completed | April 2, 2026, 5:48 a.m. |
Created at: March 30, 2026, 6:06 p.m.