Triple
T9858625
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blue I |
E239649
|
entity |
| Predicate | titleInFrench |
P6538
|
FINISHED |
| Object | Bleu I |
E239649
|
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: Bleu I | Statement: [Blue I, titleInFrench, Bleu I]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bleu I Context triple: [Blue I, titleInFrench, Bleu I]
-
A.
Blue I
chosen
Blue I is a famous abstract painting by Spanish artist Joan Miró, characterized by its minimal composition and vivid use of blue to evoke a sense of cosmic space and poetic simplicity.
-
B.
Bleu noir
Bleu noir is a 2010 studio album by French singer-songwriter Mylène Farmer that blends pop, electronic, and dark atmospheric influences.
-
C.
Fil Bleu
Fil Bleu is the public transport operator responsible for running bus and tram services in and around the city of Tours, France.
-
D.
Blau
The Blau is a small river in the German state of Baden-Württemberg that flows through the city of Blaustein before joining the Danube.
-
E.
Nu bleu
Nu bleu is a famous series of blue-hued nude cut-out artworks by Henri Matisse, emblematic of his late-career paper cut-out technique.
- 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_69ca84e6493081909cf58c8d42ea856b |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb399bd8081908281d1735cc3909f |
completed | April 2, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1e43b2de881909e00f6701d1c7b54 |
completed | April 5, 2026, 4:25 a.m. |
Created at: March 30, 2026, 8:35 p.m.