Triple
T8720008
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TER Bretagne |
E206986
|
entity |
| Predicate | connectsCity |
P4245
|
FINISHED |
| Object | Redon |
E393208
|
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: Redon | Statement: [TER Bretagne, connectsCity, Redon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Redon Context triple: [TER Bretagne, connectsCity, Redon]
-
A.
Redon
Redon is a French surname most notably associated with the Symbolist painter and printmaker Odilon Redon.
-
B.
Redon
chosen
Redon is a small historic town in western France known for its canal junction and medieval abbey, situated near the borders of Brittany and Pays de la Loire.
-
C.
Murillo
Murillo was a prominent 17th-century Spanish Baroque painter renowned for his religious works and tender, luminous depictions of everyday life.
-
D.
Murillo
Murillo is a small Colombian town in the Tolima department, known as a gateway for trekking and mountaineering in the Los Nevados National Natural Park.
-
E.
Diéguez
Diéguez is a Spanish-language surname of Galician origin borne by various notable individuals, including figures in the arts and public life.
- 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_69ca835811d8819081ea00fd2a2c9a1c |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5d02a52c81909f93622ae6920b80 |
completed | March 31, 2026, 11:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf28f599a481908e93bc5b5c41296e |
completed | April 3, 2026, 2:41 a.m. |
Created at: March 30, 2026, 6:36 p.m.