Triple
T266277
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Water Lilies (Monet) |
E5735
|
entity |
| Predicate | number of works |
P5764
|
FINISHED |
| Object | approximately 250 |
—
|
LITERAL 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: approximately 250 | Statement: [Water Lilies (Monet), number of works, approximately 250]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: number of works Context triple: [Water Lilies (Monet), number of works, approximately 250]
-
A.
numberOfWorks
Indicates the total count of works associated with a given entity.
-
B.
numberOfWorksCreated
Indicates the total count of creative works that an entity has produced or authored.
-
C.
yearWorkWritten
Indicates the year in which a particular work was written or created.
-
D.
notableWork
Indicates that one entity is a significant or well-known work (such as a book, artwork, or creation) produced by another entity.
-
E.
estimatedNumberOfPaintings
chosen
Indicates the approximate count of paintings associated with an entity, rather than an exact, verified number.
- F. None of above.
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_69a2587daeb081909591b9d30f80a271 |
completed | Feb. 28, 2026, 2:52 a.m. |
| NER | Named-entity recognition | batch_69a25d90bab48190b3ef97a451653b7f |
completed | Feb. 28, 2026, 3:14 a.m. |
| PD | Predicate disambiguation | batch_69a25b6f60b081908fc6467800a8849e |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:56 a.m.