Triple
T2505092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Allier |
E52558
|
entity |
| Predicate | hasTributary |
P415
|
FINISHED |
| Object |
Chapeauroux
Chapeauroux is a river in central France that flows through the Massif Central before joining the Allier.
|
E304936
|
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: Chapeauroux | Statement: [Allier, hasTributary, Chapeauroux]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chapeauroux Context triple: [Allier, hasTributary, Chapeauroux]
-
A.
Châteauroux
Châteauroux is a city in central France that will host the shooting events for the 2024 Summer Olympics.
-
B.
Bourges
Bourges is a historic city in central France known for its well-preserved medieval architecture and its UNESCO-listed Gothic cathedral, Saint-Étienne.
-
C.
Mâcon
Mâcon is a historic town in eastern France’s Burgundy region, known for its wine production and picturesque setting along the Saône River.
-
D.
Montluçon
Montluçon is a historic industrial town in central France known for its medieval old quarter and role as a key urban center in the Allier department.
-
E.
Guéret
Guéret is a small city in central France that serves as the capital of the Creuse department in the Nouvelle-Aquitaine region.
- 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: Chapeauroux Triple: [Allier, hasTributary, Chapeauroux]
Generated description
Chapeauroux is a river in central France that flows through the Massif Central before joining the Allier.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Chapeauroux Target entity description: Chapeauroux is a river in central France that flows through the Massif Central before joining the Allier.
-
A.
Châteauroux
Châteauroux is a city in central France that will host the shooting events for the 2024 Summer Olympics.
-
B.
Bourges
Bourges is a historic city in central France known for its well-preserved medieval architecture and its UNESCO-listed Gothic cathedral, Saint-Étienne.
-
C.
Mâcon
Mâcon is a historic town in eastern France’s Burgundy region, known for its wine production and picturesque setting along the Saône River.
-
D.
Montluçon
Montluçon is a historic industrial town in central France known for its medieval old quarter and role as a key urban center in the Allier department.
-
E.
Guéret
Guéret is a small city in central France that serves as the capital of the Creuse department in the Nouvelle-Aquitaine region.
- 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_69ab4957b3a88190adf968ae0c1b931c |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd1cec9f48190848b6129aa394ce4 |
completed | March 7, 2026, 7:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b01d1c73d88190b4e871b9876e1a52 |
completed | March 10, 2026, 1:31 p.m. |
| NEDg | Description generation | batch_69b0212016f881909e7ce8726680f40f |
completed | March 10, 2026, 1:48 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b022213c6c81909549e5c46991f4a9 |
completed | March 10, 2026, 1:52 p.m. |
Created at: March 6, 2026, 9:46 p.m.