Triple
T2868172
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Violet Attlee |
E63491
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Violet |
E75564
|
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: Violet | Statement: [Violet Attlee, givenName, Violet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Violet Context triple: [Violet Attlee, givenName, Violet]
-
A.
Violet
chosen
Violet is a small, typically purple-flowered plant commonly found in temperate regions and widely recognized as a symbol of modesty and springtime.
-
B.
Violeta
Violeta is a novel by Chilean author Isabel Allende that follows the tumultuous, century-long life of a woman born during the 1918 Spanish flu pandemic.
-
C.
Rosamorada
Rosamorada is a municipality and town in the Mexican state of Nayarit, known for its agricultural activities and rural communities.
-
D.
Black and Violet
"Black and Violet" is an abstract painting by Wassily Kandinsky that exemplifies his pioneering use of color and geometric forms to evoke emotional and spiritual responses.
-
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.
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_69ab4c42fb8c8190b36e161d47c03b81 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdfdfef1881909dc52a1b34cd24e3 |
completed | March 7, 2026, 8:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b01dabb19c8190822ac992ab764446 |
completed | March 10, 2026, 1:33 p.m. |
Created at: March 6, 2026, 10:02 p.m.