Triple
T11843382
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CA Portes de France–Thionville |
E281709
|
entity |
| Predicate | includesCommune |
P15149
|
FINISHED |
| Object | Cattenom |
E824991
|
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: Cattenom | Statement: [CA Portes de France–Thionville, includesCommune, Cattenom]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cattenom Context triple: [CA Portes de France–Thionville, includesCommune, Cattenom]
-
A.
Cattenom
chosen
Cattenom is a French commune in northeastern France best known for hosting one of the country's largest nuclear power plants.
-
B.
Sarreguemines
Sarreguemines is a town in northeastern France near the German border, historically known for its ceramics and faience production.
-
C.
Pont-à-Mousson
Pont-à-Mousson is a historic town in northeastern France on the Moselle River, known for its medieval heritage and former university.
-
D.
Sarrebourg
Sarrebourg is a small historic town in northeastern France known for its cultural heritage and location in the Moselle department of the Grand Est region.
-
E.
Couvin
Couvin is a municipality in southern Belgium known for its extensive forests, caves, and rural landscapes within the Walloon region.
- 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_69d6ab287ba48190a5178779fd19b9b7 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a65a597c8190b09f57463b279afc |
completed | April 10, 2026, 7:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f4716d92c881908d45cb7b3babb1f7 |
completed | May 1, 2026, 9:25 a.m. |
Created at: April 8, 2026, 9:43 p.m.