Triple
T31354957
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Musée Fernand Léger – André Mare |
E799702
|
entity |
| Predicate | highlightsContributionOf |
P477
|
FINISHED |
| Object | Fernand Léger |
—
|
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: Fernand Léger | Statement: [Musée Fernand Léger – André Mare, highlightsContributionOf, Fernand Léger]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: highlightsContributionOf Context triple: [Musée Fernand Léger – André Mare, highlightsContributionOf, Fernand Léger]
-
A.
highlights
Indicates that one entity draws special attention to, emphasizes, or visually marks another entity as important or noteworthy.
-
B.
notableContribution
chosen
Indicates that an entity has made a significant, recognized contribution to another entity, field, work, or endeavor.
-
C.
portraysContribution
Indicates that one entity depicts, represents, or illustrates the contribution or role of another entity.
-
D.
highlightsSign
Indicates that one entity visually emphasizes or draws special attention to a sign.
-
E.
highlightsAttributeOf
Indicates that one entity draws attention to, emphasizes, or showcases a particular attribute or property of another entity.
- 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_69f224e5e9bc8190a16339328897c4f8 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69f4533d08190af2673906bd73088 |
completed | May 3, 2026, 1:05 a.m. |
| PD | Predicate disambiguation | batch_69f69d1d25e88190a7f57d323574da90 |
completed | May 3, 2026, 12:55 a.m. |
Created at: April 29, 2026, 9:17 p.m.