Triple
T1977474
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Danse (1909–1910) |
E42947
|
entity |
| Predicate | numberOfHumanFigures |
P6685
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [La Danse (1909–1910), numberOfHumanFigures, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfHumanFigures Context triple: [La Danse (1909–1910), numberOfHumanFigures, 5]
-
A.
numberOfFiguresDepicted
chosen
Indicates the total count of distinct figures shown within a given depiction or representation.
-
B.
largestFigureLengthApprox
Indicates an approximate measurement of the length of the largest figure involved in the relationship or context.
-
C.
numberOfSculptures
Indicates the quantity of sculptures associated with a given entity or context.
-
D.
numberOfHumanProtagonists
Indicates the count of human characters that serve as protagonists in a given work or context.
-
E.
numberOfCharacters
Indicates the total count of individual characters present in a given text, string, or entity’s representation.
- 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_69a8871289048190b00b0d7744b7b2b1 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb42ecde881909bc9132885d8d0bd |
completed | March 7, 2026, 5:14 a.m. |
| PD | Predicate disambiguation | batch_69abaff9a09c8190a81fa13f4b85bc79 |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:36 p.m.