Triple

T7763607
Position Surface form Disambiguated ID Type / Status
Subject Marnes-la-Coquette E176086 entity
Predicate namedAfter P63 FINISHED
Object Marnes
Marnes is a historical locality in France whose name survives in the modern commune of Marnes-la-Coquette.
E527753 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: Marnes | Statement: [Marnes-la-Coquette, namedAfter, Marnes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marnes
Context triple: [Marnes-la-Coquette, namedAfter, Marnes]
  • A. Maringe
    Maringe is an alternate name for the Cheke Holo language spoken in the Solomon Islands.
  • B. Mont-Saint-Martin
    Mont-Saint-Martin is a commune in northeastern France notable for lying at the junction of the French, Belgian, and Luxembourgish borders.
  • C. Maurepas
    Maurepas is a commune in the Yvelines department in the Île-de-France region of north-central France, known as a residential suburb southwest of Paris.
  • D. Mitry–Claye
    Mitry–Claye is a suburban railway station in the northeastern outskirts of Paris that serves as one of the terminal endpoints of the RER B commuter line.
  • E. Marnes-la-Coquette
    Marnes-la-Coquette is a small, affluent residential commune in the western suburbs of Paris, known for its wooded surroundings and proximity to the Parc de Saint-Cloud.
  • 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: Marnes
Triple: [Marnes-la-Coquette, namedAfter, Marnes]
Generated description
Marnes is a historical locality in France whose name survives in the modern commune of Marnes-la-Coquette.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Marnes
Target entity description: Marnes is a historical locality in France whose name survives in the modern commune of Marnes-la-Coquette.
  • A. Maringe
    Maringe is an alternate name for the Cheke Holo language spoken in the Solomon Islands.
  • B. Mont-Saint-Martin
    Mont-Saint-Martin is a commune in northeastern France notable for lying at the junction of the French, Belgian, and Luxembourgish borders.
  • C. Maurepas
    Maurepas is a commune in the Yvelines department in the Île-de-France region of north-central France, known as a residential suburb southwest of Paris.
  • D. Mitry–Claye
    Mitry–Claye is a suburban railway station in the northeastern outskirts of Paris that serves as one of the terminal endpoints of the RER B commuter line.
  • E. Marnes-la-Coquette chosen
    Marnes-la-Coquette is a small, affluent residential commune in the western suburbs of Paris, known for its wooded surroundings and proximity to the Parc de Saint-Cloud.
  • F. None of above.

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_69c69962923c8190ac74d28b4f9fe0a0 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c704061d1881909b5b42bb93d2b8a7 completed March 27, 2026, 10:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8c7da8b848190b378f694118dfa19 completed March 29, 2026, 6:34 a.m.
NEDg Description generation batch_69c8c8d7a51481908fd537dbb57a6116 completed March 29, 2026, 6:38 a.m.
NED2 Entity disambiguation (via description) batch_69c8c98179908190a68b7f029fff8e3c completed March 29, 2026, 6:41 a.m.
Created at: March 27, 2026, 4:09 p.m.