Triple
T6671633
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vincent van Gogh |
E151743
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Irises |
E20023
|
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: Irises | Statement: [Vincent van Gogh, notableWork, Irises]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Irises Context triple: [Vincent van Gogh, notableWork, Irises]
-
A.
Irises
chosen
Irises is a famous 1889 oil painting by Vincent van Gogh depicting a vibrant cluster of blooming irises, celebrated for its expressive color and dynamic composition.
-
B.
Iris
Iris is the underage prostitute whom Travis Bickle becomes obsessed with rescuing in Martin Scorsese’s film "Taxi Driver."
-
C.
Iris
"Iris" is a hit power ballad by the Goo Goo Dolls, best known for its prominent feature on the soundtrack of the film "City of Angels."
-
D.
Iris
Iris is a recurring character on the satirical sketch comedy series "Portlandia," known for embodying the show's quirky, offbeat humor.
-
E.
Iris
Iris is a powerful, genetically engineered kaiju and one of Gamera’s most formidable adversaries in the Heisei-era Gamera film series.
- 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_69c687f71fc081909dbd45d6377f6045 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6b0ca49f88190b9c8e0f641be0c3f |
completed | March 27, 2026, 4:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6ef14b47c8190ac181f272025fb0d |
completed | March 27, 2026, 8:56 p.m. |
Created at: March 27, 2026, 2:03 p.m.