Triple
T15670598
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RN12 |
E377299
|
entity |
| Predicate | connectsTown |
P845
|
FINISHED |
| Object | Fougères |
E191224
|
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: Fougères | Statement: [RN12, connectsTown, Fougères]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fougères Context triple: [RN12, connectsTown, Fougères]
-
A.
Fougères
chosen
Fougères is a historic town in Brittany, northwestern France, known for its impressive medieval castle and well-preserved old quarter.
-
B.
Fallières
Fallières is a French surname most notably borne by Armand Fallières, who served as President of France in the early 20th century.
-
C.
Fremault
Fremault is the surname of American film and television actress Anita Louise.
-
D.
Villefontaine
Villefontaine is a commune in the Isère department of southeastern France, known as a suburban town within the Grenoble urban area.
-
E.
Langres
Langres is a historic fortified town in northeastern France known for its well-preserved ramparts and as the birthplace of Enlightenment philosopher Denis Diderot.
- 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_69d85cd2e28481909d4e975bee20872f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04f1254508190a77a16b7bfd299ad |
completed | April 16, 2026, 2:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00b274fa3481908b019036cd2ae627 |
completed | May 10, 2026, 4:29 p.m. |
Created at: April 10, 2026, 4:16 a.m.