Triple
T9006139
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eugene Ormandy |
E215147
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Blau |
E199596
|
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: Blau | Statement: [Eugene Ormandy, familyName, Blau]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Blau Context triple: [Eugene Ormandy, familyName, Blau]
-
A.
Blau
chosen
The Blau is a small river in the German state of Baden-Württemberg that flows through the city of Blaustein before joining the Danube.
-
B.
Blå
Blå is a renowned live music and cultural venue in Oslo, Norway, known for its vibrant jazz, electronic, and alternative music scene.
-
C.
Blågult
Blågult is the popular Swedish nickname for the Sweden women's national football team, referencing the country's blue and yellow colors.
-
D.
Borouge
Borouge is a leading petrochemicals company based in the United Arab Emirates, specializing in the production of polyolefins for packaging, infrastructure, and industrial applications.
-
E.
Bleu noir
Bleu noir is a 2010 studio album by French singer-songwriter Mylène Farmer that blends pop, electronic, and dark atmospheric influences.
- 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_69ca83a12d648190b1e4fe11e8a31890 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc69bc6e208190b0c01e3761c04799 |
completed | April 1, 2026, 12:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfd0e7f090819093c7af51c3979978 |
completed | April 3, 2026, 2:38 p.m. |
Created at: March 30, 2026, 7:05 p.m.