Triple

T10043395
Position Surface form Disambiguated ID Type / Status
Subject Coesfeld E205349 entity
Predicate hasTwinTown P919 FINISHED
Object Plerguer
Plerguer is a small commune in the Ille-et-Vilaine department of Brittany in northwestern France.
 E837616 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: Plerguer | Statement: [Coesfeld, hasTwinTown, Plerguer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Plerguer
Context triple: [Coesfeld, hasTwinTown, Plerguer]
  • A. Guerlinguetus
    Guerlinguetus is a genus of tree squirrels within the tribe Sciurini, comprising several Neotropical squirrel species.
  • B. Raguil
    Raguil is an alternative spelling of Raguel, a traditional archangel name found in various Judeo-Christian angelologies.
  • C. Pagnerre
    Pagnerre was a 19th-century French publishing house known for issuing major literary works, including those of Victor Hugo.
  • D. Lemerig
    Lemerig is an endangered Oceanic language spoken by a small community on the island of Vanua Lava in northern Vanuatu.
  • E. Tergnier
    Tergnier is a commune in northern France known historically as a significant railway junction and industrial town in the Aisne department.
  • 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: Plerguer
Triple: [Coesfeld, hasTwinTown, Plerguer]
Generated description
Plerguer is a small commune in the Ille-et-Vilaine department of Brittany in northwestern France.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Plerguer
Target entity description: Plerguer is a small commune in the Ille-et-Vilaine department of Brittany in northwestern France.
  • A. Guerlinguetus
    Guerlinguetus is a genus of tree squirrels within the tribe Sciurini, comprising several Neotropical squirrel species.
  • B. Raguil
    Raguil is an alternative spelling of Raguel, a traditional archangel name found in various Judeo-Christian angelologies.
  • C. Pagnerre
    Pagnerre was a 19th-century French publishing house known for issuing major literary works, including those of Victor Hugo.
  • D. Lemerig
    Lemerig is an endangered Oceanic language spoken by a small community on the island of Vanua Lava in northern Vanuatu.
  • E. Tergnier
    Tergnier is a commune in northern France known historically as a significant railway junction and industrial town in the Aisne department.
  • 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_69ca834f70e88190b2d74828b7767ec1 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cdcf60a2208190846e57b5f5649307 completed April 2, 2026, 2:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69d28278235c8190a5e833a9586bd3f5 completed April 5, 2026, 3:40 p.m.
NEDg Description generation batch_69d28391f8fc8190964cdccaf5625617 completed April 5, 2026, 3:45 p.m.
NED2 Entity disambiguation (via description) batch_69d284604dc88190b452ee847d3390dd completed April 5, 2026, 3:48 p.m.
Created at: March 30, 2026, 8:55 p.m.