Triple
T10340195
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bob Rafelson |
E243107
|
entity |
| Predicate | directed |
P7373
|
FINISHED |
| Object | Blood and Wine |
E858255
|
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: Blood and Wine | Statement: [Bob Rafelson, directed, Blood and Wine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Blood and Wine Context triple: [Bob Rafelson, directed, Blood and Wine]
-
A.
Blood and Wine
chosen
Blood and Wine is a 1996 neo-noir crime thriller film directed by Bob Rafelson and starring Jack Nicholson, Michael Caine, and Jennifer Lopez.
-
B.
Bitter Wine
"Bitter Wine" is a song featured on the album "These Days."
-
C.
The Wine Drinker
The Wine Drinker is a genre painting by Dutch Golden Age artist Jan van der Meer van Utrecht, depicting a convivial scene centered on a figure enjoying wine.
-
D.
The Red Vineyard
The Red Vineyard is an 1888 oil painting by Vincent van Gogh, celebrated as the only work he is known to have sold during his lifetime and depicting laborers harvesting grapes in the glowing light of sunset.
-
E.
La Soif
La Soif is the debut novel of Algerian writer Assia Djebar, exploring themes of female identity, desire, and colonial society in mid-20th-century Algeria.
- 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_69d381af787481908bc401325c760a88 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e0a526a08190afe7091a0cf1f073 |
completed | April 7, 2026, 10:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d79508427c81909db511e969bc9ddb |
completed | April 9, 2026, 12:01 p.m. |
Created at: April 6, 2026, 11:54 a.m.