Triple
T1600763
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Franche-Comté |
E34385
|
entity |
| Predicate | containsDepartment |
P1467
|
FINISHED |
| Object | Doubs |
E137004
|
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: Doubs | Statement: [Franche-Comté, containsDepartment, Doubs]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Doubs Context triple: [Franche-Comté, containsDepartment, Doubs]
-
A.
Doubs River
chosen
The Doubs River is a major river in eastern France and western Switzerland, known for its winding course through the Jura Mountains and its scenic gorges, waterfalls, and hydroelectric dams.
-
B.
Rhône
Rhône is a department in eastern France named after the Rhône River, known for its capital city Lyon and its significant role in the country's economic and cultural life.
-
C.
Isère River
The Isère River is a significant waterway in southeastern France that flows through the Alps and the city of Grenoble before joining the Rhône.
-
D.
Ouvèze River
The Ouvèze River is a river in southeastern France that flows through the Drôme and Vaucluse departments before joining the Rhône.
-
E.
Isère
Isère is a department in southeastern France known for its Alpine landscapes, winter sports resorts, and the city of Grenoble.
- 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_69a885fdcb9c819081ce6f0b8cd477dd |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a9094a27908190bf0d9b5d43617192 |
completed | March 5, 2026, 4:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af6529905081909bd9e7c51fc21f77 |
completed | March 10, 2026, 12:26 a.m. |
Created at: March 4, 2026, 7:28 p.m.