Triple
T4490214
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Valdigne |
E107352
|
entity |
| Predicate | river |
P165
|
FINISHED |
| Object | Dora Baltea |
E429981
|
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: Dora Baltea | Statement: [Valdigne, river, Dora Baltea]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dora Baltea Context triple: [Valdigne, river, Dora Baltea]
-
A.
Dora Baltea
chosen
Dora Baltea is a major river in northwestern Italy that flows from the Alps through the Aosta Valley and Piedmont before joining the Po River.
-
B.
Dora Luz
Dora Luz was a Mexican singer and actress best known for her musical performances in classic Disney films of the 1940s.
-
C.
Dora
Dora is the given name of Dora Sigerson Shorter, an Irish poet associated with the late 19th- and early 20th-century literary revival.
-
D.
Dora
Dora is a character in Jim Jarmusch’s film "Broken Flowers," known as one of Don Johnston’s former girlfriends whom he visits while searching for the mother of his alleged son.
-
E.
Dora Riparia
Dora Riparia is a river in northwestern Italy that flows through the city of Turin before joining the Po River.
- 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_69bd43f84f788190a1383579c4a595be |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd556d29f08190bab1e872dd7e819f |
completed | March 20, 2026, 2:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bd67aee5908190888efb94eee725e5 |
completed | March 20, 2026, 3:28 p.m. |
Created at: March 20, 2026, 12:59 p.m.