Triple

T3141469
Position Surface form Disambiguated ID Type / Status
Subject canton of Mitry-Mory E65654 entity
Predicate containsCommune P15149 FINISHED
Object Nantouillet
Nantouillet is a small rural commune in the Seine-et-Marne department in the Île-de-France region of north-central France.
 E392068 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: Nantouillet | Statement: [canton of Mitry-Mory, containsCommune, Nantouillet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nantouillet
Context triple: [canton of Mitry-Mory, containsCommune, Nantouillet]
  • A. Aiguillon
    Aiguillon is a commune in southwestern France, known for its strategic location at the confluence of the Lot and Garonne rivers.
  • B. Patouès
    Patouès is a regional Romance dialect of the Franco-Provençal language traditionally spoken in parts of France, Switzerland, and Italy.
  • C. Ducos
    Ducos is a French surname most notably borne by Pierre-Roger Ducos, a political figure during the French Revolution and the Consulate.
  • D. Laumière
    Laumière is a Paris Métro station on the city’s northeastern side, located in the 19th arrondissement near the Canal de l’Ourcq.
  • E. Largentière
    Largentière is a historic town in southern France known for its medieval architecture and former silver mining industry.
  • 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: Nantouillet
Triple: [canton of Mitry-Mory, containsCommune, Nantouillet]
Generated description
Nantouillet is a small rural commune in the Seine-et-Marne department in the Île-de-France region of north-central France.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nantouillet
Target entity description: Nantouillet is a small rural commune in the Seine-et-Marne department in the Île-de-France region of north-central France.
  • A. Aiguillon
    Aiguillon is a commune in southwestern France, known for its strategic location at the confluence of the Lot and Garonne rivers.
  • B. Patouès
    Patouès is a regional Romance dialect of the Franco-Provençal language traditionally spoken in parts of France, Switzerland, and Italy.
  • C. Ducos
    Ducos is a French surname most notably borne by Pierre-Roger Ducos, a political figure during the French Revolution and the Consulate.
  • D. Laumière
    Laumière is a Paris Métro station on the city’s northeastern side, located in the 19th arrondissement near the Canal de l’Ourcq.
  • E. Largentière
    Largentière is a historic town in southern France known for its medieval architecture and former silver mining industry.
  • 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_69ad8582f564819088c27e1f96153938 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada57895dc8190bd3d4ef9391973dc completed March 8, 2026, 4:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69b503d3f19c819088061d3c68757957 completed March 14, 2026, 6:44 a.m.
NEDg Description generation batch_69b50523dbb08190b1fd089092c1b2a6 completed March 14, 2026, 6:50 a.m.
NED2 Entity disambiguation (via description) batch_69b50594e4888190b2db45eee2a988a7 completed March 14, 2026, 6:52 a.m.
Created at: March 8, 2026, 3:05 p.m.