Triple
T8797410
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Usingen |
E209322
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object |
Chassieu
Chassieu is a commune in the Metropolis of Lyon in eastern France, known for its residential areas and proximity to the Lyon urban center.
|
E776809
|
NE FINISHED |
How this triple was built (4 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: Chassieu | Statement: [Usingen, hasTwinTown, Chassieu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chassieu Context triple: [Usingen, hasTwinTown, Chassieu]
-
A.
Saignelégier
Saignelégier is a municipality in the Swiss canton of Jura known for its rural landscapes, watchmaking heritage, and the annual Marché-Concours horse festival.
-
B.
Cugny
Cugny is a locality within the municipality of Bernex in the canton of Geneva, Switzerland.
-
C.
Gueugnon
Gueugnon is a small commune in eastern France known historically for its steel industry and location in the Bourgogne-Franche-Comté region.
-
D.
Chêne-Bougeries
Chêne-Bougeries is a suburban municipality in western Switzerland, located just east of the city of Geneva in the canton of Geneva.
-
E.
Voiron
Voiron is a commune in southeastern France known for its historical town center and proximity to the Chartreuse Mountains.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Chassieu Triple: [Usingen, hasTwinTown, Chassieu]
Generated description
Chassieu is a commune in the Metropolis of Lyon in eastern France, known for its residential areas and proximity to the Lyon urban center.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Chassieu Target entity description: Chassieu is a commune in the Metropolis of Lyon in eastern France, known for its residential areas and proximity to the Lyon urban center.
-
A.
Saignelégier
Saignelégier is a municipality in the Swiss canton of Jura known for its rural landscapes, watchmaking heritage, and the annual Marché-Concours horse festival.
-
B.
Cugny
Cugny is a locality within the municipality of Bernex in the canton of Geneva, Switzerland.
-
C.
Gueugnon
Gueugnon is a small commune in eastern France known historically for its steel industry and location in the Bourgogne-Franche-Comté region.
-
D.
Chêne-Bougeries
Chêne-Bougeries is a suburban municipality in western Switzerland, located just east of the city of Geneva in the canton of Geneva.
-
E.
Voiron
Voiron is a commune in southeastern France known for its historical town center and proximity to the Chartreuse Mountains.
- F. None of above. chosen
Provenance (5 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_69ca836240888190a62b262e56a69d2f |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5fa370d08190885ef65e3a3e56d3 |
completed | March 31, 2026, 11:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cffd6b7eb88190b878165e41cf1df8 |
completed | April 3, 2026, 5:48 p.m. |
| NEDg | Description generation | batch_69d003903e188190aed2683d969602b9 |
completed | April 3, 2026, 6:14 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d003fba47c819087a2be245fc9da6a |
completed | April 3, 2026, 6:16 p.m. |
Created at: March 30, 2026, 6:44 p.m.