Triple
T11027043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Donn Cambern |
E260651
|
entity |
| Predicate | editedFilm |
P14416
|
FINISHED |
| Object | The Sicilian |
E423976
|
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: The Sicilian | Statement: [Donn Cambern, editedFilm, The Sicilian]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Sicilian Context triple: [Donn Cambern, editedFilm, The Sicilian]
-
A.
The Sicilian
chosen
The Sicilian is a novel by Mario Puzo that expands the world of The Godfather through the story of a legendary Sicilian bandit and his ties to the Corleone family.
-
B.
The Sicilian
The Sicilian is a character in Henry Wadsworth Longfellow’s narrative poem collection "Tales of a Wayside Inn," known for contributing stories that reflect his cultural background and experiences.
-
C.
Benoni
Benoni is a large town in South Africa’s Gauteng province, situated on the East Rand within the Greater Johannesburg metropolitan area and known historically for its gold mining and lakes.
-
D.
Srbobran
Srbobran is a town and municipality in northern Serbia known for its agricultural economy and multicultural heritage.
-
E.
Saxe – Gambetta
Saxe – Gambetta is a major interchange station in the Lyon Metro system, serving as a key hub between multiple lines near the city center.
- 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_69d6aa9687448190b28d353b1b6a610e |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d797d190f08190bcb5949ee24306f1 |
completed | April 9, 2026, 12:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3753451e08190bc42ab99d01926f9 |
completed | April 18, 2026, 12:12 p.m. |
Created at: April 8, 2026, 9:25 p.m.