Triple
T95603
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rhône River |
E1922
|
entity |
| Predicate | cityOnRiver |
P165
|
FINISHED |
| Object | Beaucaire |
E11137
|
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: Beaucaire | Statement: [Rhône River, cityOnRiver, Beaucaire]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beaucaire Context triple: [Rhône River, cityOnRiver, Beaucaire]
-
A.
Bordeaux
Bordeaux is a renowned wine-producing region in southwestern France, famous for its prestigious red blends and long winemaking tradition.
-
B.
Vichy
Vichy is a spa town in central France renowned for its thermal springs, health resorts, and role as the seat of the World War II Vichy regime.
-
C.
Tarascon
chosen
Tarascon is a historic town in southern France, known for its medieval castle and Provençal heritage along the lower Rhône Valley.
-
D.
Saint-Genis-Pouilly
Saint-Genis-Pouilly is a French commune in the Ain department near the Swiss border, known for its proximity to Geneva and the CERN research center.
-
E.
Reims
Reims is a historic city in northeastern France known for its Gothic cathedral, role in French coronations, and significance during both World Wars.
- 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_69a24d4862f881908cc8b89d3a78031d |
completed | Feb. 28, 2026, 2:04 a.m. |
| NER | Named-entity recognition | batch_69a256a7957c8190bf9924eff7572b95 |
completed | Feb. 28, 2026, 2:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a29e45d6488190bc982137255c79f9 |
completed | Feb. 28, 2026, 7:50 a.m. |
Created at: Feb. 28, 2026, 2:09 a.m.