Triple
T3189137
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Semois River |
E66774
|
entity |
| Predicate | mouthLocation |
P417
|
FINISHED |
| Object | Monthermé |
E346792
|
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: Monthermé | Statement: [Semois River, mouthLocation, Monthermé]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Monthermé Context triple: [Semois River, mouthLocation, Monthermé]
-
A.
Monthermé
chosen
Monthermé is a commune in northeastern France’s Ardennes department, known for its scenic setting at the confluence of forested valleys and winding rivers.
-
B.
Laumière
Laumière is a Paris Métro station on the city’s northeastern side, located in the 19th arrondissement near the Canal de l’Ourcq.
-
C.
Bouzeron
Bouzeron is a small appellation in Burgundy, France, particularly noted for producing distinctive white wines from the Aligoté grape.
-
D.
Oyonnax
Oyonnax is a town in eastern France’s Ain department, known historically for its plastics industry and its role in the French Resistance during World War II.
-
E.
Sorgues
Sorgues is a commune in southeastern France’s Vaucluse department, known for its location near Avignon and its position at the confluence of the Ouvèze and Sorgue rivers.
- 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_69ad8587c1bc8190a2595f2c22ee1001 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada6e491508190bc881feaee3889bc |
completed | March 8, 2026, 4:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b31a63fb6081909a7a15cf8a03e52e |
completed | March 12, 2026, 7:56 p.m. |
Created at: March 8, 2026, 3:06 p.m.