Triple
T3125439
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Evidence |
E65284
|
entity |
| Predicate | collaboratedWith |
P435
|
FINISHED |
| Object | Blu |
unclear NED1
|
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: Blu | Statement: [Evidence, collaboratedWith, Blu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Blu Context triple: [Evidence, collaboratedWith, Blu]
-
A.
Blu
Blu is a popular electronic cigarette and vaping brand known for its range of rechargeable and disposable e-cigarette products.
-
B.
Blu
Blu is a domesticated Spix's macaw who serves as the timid yet brave protagonist of the animated Rio film series.
-
C.
Blum
Blum is a surname of German and Jewish origin borne by various notable individuals across fields such as mathematics, politics, and the arts.
-
D.
Blix
Blix is a Swedish surname most notably associated with Hans Blix, the former head of the International Atomic Energy Agency and UN weapons inspector.
-
E.
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.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
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_69ad8580c72481909672d37acf647893 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada52e9f348190aa15b2c0d252719f |
completed | March 8, 2026, 4:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b20f75fbf081909a2957b7277c3aae |
completed | March 12, 2026, 12:57 a.m. |
Created at: March 8, 2026, 3:04 p.m.