Triple
T1438069
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barnstaple |
E31001
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object |
Hennebont
Hennebont is a historic town in the Morbihan department of Brittany in northwestern France, known for its medieval ramparts and cultural heritage.
|
E194476
|
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: Hennebont | Statement: [Barnstaple, hasTwinTown, Hennebont]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hennebont Context triple: [Barnstaple, hasTwinTown, Hennebont]
-
A.
Fougères
Fougères is a historic town in Brittany, northwestern France, known for its impressive medieval castle and well-preserved old quarter.
-
B.
Remire-Montjoly
Remire-Montjoly is a coastal commune in northeastern South America, forming part of the urban area of Cayenne in French Guiana and known for its beaches and residential character.
-
C.
Quimper
Quimper is a historic city in western France known for its medieval old town, Gothic cathedral, and traditional Breton culture.
-
D.
Vannes
Vannes is a historic coastal city in northwestern France known for its well-preserved medieval old town and harbor on the Gulf of Morbihan.
-
E.
Boncourt
Boncourt is a locality known for its historic Château de Boncourt, reflecting its cultural and architectural heritage.
- 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: Hennebont Triple: [Barnstaple, hasTwinTown, Hennebont]
Generated description
Hennebont is a historic town in the Morbihan department of Brittany in northwestern France, known for its medieval ramparts and cultural heritage.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hennebont Target entity description: Hennebont is a historic town in the Morbihan department of Brittany in northwestern France, known for its medieval ramparts and cultural heritage.
-
A.
Fougères
Fougères is a historic town in Brittany, northwestern France, known for its impressive medieval castle and well-preserved old quarter.
-
B.
Remire-Montjoly
Remire-Montjoly is a coastal commune in northeastern South America, forming part of the urban area of Cayenne in French Guiana and known for its beaches and residential character.
-
C.
Quimper
Quimper is a historic city in western France known for its medieval old town, Gothic cathedral, and traditional Breton culture.
-
D.
Vannes
Vannes is a historic coastal city in northwestern France known for its well-preserved medieval old town and harbor on the Gulf of Morbihan.
-
E.
Boncourt
Boncourt is a locality known for its historic Château de Boncourt, reflecting its cultural and architectural heritage.
- 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_69a4991633388190a4d61b5a98aa407a |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c5059ef88190af20e796acdb2058 |
completed | March 1, 2026, 11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad8aad1a30819086df8e4ef3752263 |
completed | March 8, 2026, 2:41 p.m. |
| NEDg | Description generation | batch_69ad979b7f2c819094c907bed705db3b |
completed | March 8, 2026, 3:36 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad9831a87c819089fc3b590ab7ecb2 |
completed | March 8, 2026, 3:39 p.m. |
Created at: March 1, 2026, 8 p.m.