Triple
T16460293
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kehrsatz |
E399787
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Saint-Léonard-de-Noblat |
E913533
|
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: Saint-Léonard-de-Noblat | Statement: [Kehrsatz, hasTwinTown, Saint-Léonard-de-Noblat]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saint-Léonard-de-Noblat Context triple: [Kehrsatz, hasTwinTown, Saint-Léonard-de-Noblat]
-
A.
Saint-Léonard-de-Noblat
chosen
Saint-Léonard-de-Noblat is a historic commune in central France renowned for its medieval architecture and pilgrimage church dedicated to Saint Leonard.
-
B.
Saint-Céré
Saint-Céré is a small historic town in the Lot department of southwestern France, known for its medieval architecture and picturesque setting in the Dordogne Valley.
-
C.
Saint-Girons
Saint-Girons is a small town in the Ariège department of southwestern France, situated in the foothills of the Pyrenees.
-
D.
Saint-Junien
Saint-Junien is a commune in west-central France known for its historical leather and glove-making industry and its location along the Vienne River.
-
E.
Blagnac
Blagnac is a suburban town near Toulouse in southwestern France, best known for hosting the headquarters and main facilities of the aircraft manufacturer Airbus.
- 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_69d87f2dac988190b74d6e185fa88ba4 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32d80e66c8190b2b3199efe9cfaa1 |
completed | April 18, 2026, 7:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a004f53aff081909a75de6672f15f0e |
completed | May 10, 2026, 9:26 a.m. |
Created at: April 10, 2026, 5:10 a.m.