Triple
T20952398
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tonino Guerra |
E516012
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Zabriskie Point |
—
|
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: Zabriskie Point | Statement: [Tonino Guerra, notableWork, Zabriskie Point]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zabriskie Point Context triple: [Tonino Guerra, notableWork, Zabriskie Point]
-
A.
Zabriskie Point
chosen
Zabriskie Point is a famous viewpoint in Death Valley National Park known for its striking eroded badlands and panoramic desert landscapes.
-
B.
Zabriskie
Zabriskie is a surname of likely Dutch origin associated with various notable individuals and families in American history.
-
C.
Zabriskie Hall
Zabriskie Hall is a historic academic building on the campus of Wells College in Aurora, New York.
-
D.
Mulholland Point
Mulholland Point is a coastal headland in New Brunswick, Canada, overlooking the Bay of Fundy near the border with the United States.
-
E.
Paradise 7
Paradise 7 is an installment in the Paradise series, a collection of works sharing a common thematic or narrative universe.
- 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_69e0b4fcd678819087a304291f14330a |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6fadf85f88190924d3919b9e665e4 |
completed | April 21, 2026, 4:19 a.m. |
Created at: April 16, 2026, 1:27 p.m.