Triple
T10953507
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | canton of Brienne-le-Château |
E258782
|
entity |
| Predicate | containsAdministrativeTerritorialEntity |
P747
|
FINISHED |
| Object |
Assencières
Assencières is a small commune in the Aube department of north-central France.
|
E910988
|
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: Assencières | Statement: [canton of Brienne-le-Château, containsAdministrativeTerritorialEntity, Assencières]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Assencières Context triple: [canton of Brienne-le-Château, containsAdministrativeTerritorialEntity, Assencières]
-
A.
Verrières
Verrières is a small French commune located within the Thiers arrondissement in the Puy-de-Dôme department of central France.
-
B.
Eygalières
Eygalières is a picturesque Provençal village in southern France, known for its stone houses, historic charm, and scenic setting amid the Alpilles hills.
-
C.
Aiguillon
Aiguillon is a commune in southwestern France, known for its strategic location at the confluence of the Lot and Garonne rivers.
-
D.
Bédarieux
Bédarieux is a commune in southern France’s Hérault department, known for its location in the Orb valley at the foothills of the Massif Central.
-
E.
Serques
Serques is a small commune in the Pas-de-Calais department in northern France, situated within the administrative area of Saint-Omer.
- 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: Assencières Triple: [canton of Brienne-le-Château, containsAdministrativeTerritorialEntity, Assencières]
Generated description
Assencières is a small commune in the Aube department of north-central France.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Assencières Target entity description: Assencières is a small commune in the Aube department of north-central France.
-
A.
Verrières
Verrières is a small French commune located within the Thiers arrondissement in the Puy-de-Dôme department of central France.
-
B.
Eygalières
Eygalières is a picturesque Provençal village in southern France, known for its stone houses, historic charm, and scenic setting amid the Alpilles hills.
-
C.
Aiguillon
Aiguillon is a commune in southwestern France, known for its strategic location at the confluence of the Lot and Garonne rivers.
-
D.
Bédarieux
Bédarieux is a commune in southern France’s Hérault department, known for its location in the Orb valley at the foothills of the Massif Central.
-
E.
Serques
Serques is a small commune in the Pas-de-Calais department in northern France, situated within the administrative area of Saint-Omer.
- 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_69d6aa88500c819097d7032ca578e74f |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d770fe4cfc81909032296c31e077f0 |
completed | April 9, 2026, 9:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e49677a2508190a113f9f24e318e48 |
completed | April 19, 2026, 8:46 a.m. |
| NEDg | Description generation | batch_69e49a97db808190aa22d6a103a13e58 |
completed | April 19, 2026, 9:04 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e49d71e81c8190af73931ed30e04be |
completed | April 19, 2026, 9:16 a.m. |
Created at: April 8, 2026, 9:23 p.m.