Triple

T9976332
Position Surface form Disambiguated ID Type / Status
Subject Loir-et-Cher E196339 entity
Predicate contains P35 FINISHED
Object Mer
Mer is a small commune in central France located in the Loir-et-Cher department, known for its proximity to the Loire River and several historic châteaux.
 E832742 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: Mer | Statement: [Loir-et-Cher, contains, Mer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mer
Context triple: [Loir-et-Cher, contains, Mer]
  • A. Mel
    Mel is a common diminutive form of the given name Carmelo.
  • B. Mir
    Mir is a traditional South Asian noble title historically used by rulers and aristocrats, particularly in regions such as Sindh under dynasties like the Talpurs.
  • C. Mir
    Mir was a Soviet and later Russian modular space station that served as a long-term research outpost in low Earth orbit from 1986 to 2001.
  • D. Mir
    Mir is a historic town in present-day Belarus, known for its multicultural heritage and the UNESCO-listed Mir Castle Complex.
  • E. Marg
    Marg is a given name, typically a shortened form of Margaret, used primarily in English-speaking contexts.
  • 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: Mer
Triple: [Loir-et-Cher, contains, Mer]
Generated description
Mer is a small commune in central France located in the Loir-et-Cher department, known for its proximity to the Loire River and several historic châteaux.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mer
Target entity description: Mer is a small commune in central France located in the Loir-et-Cher department, known for its proximity to the Loire River and several historic châteaux.
  • A. Mel
    Mel is a common diminutive form of the given name Carmelo.
  • B. Mir
    Mir is a traditional South Asian noble title historically used by rulers and aristocrats, particularly in regions such as Sindh under dynasties like the Talpurs.
  • C. Mir
    Mir is a historic town in present-day Belarus, known for its multicultural heritage and the UNESCO-listed Mir Castle Complex.
  • D. Mir
    Mir was a Soviet and later Russian modular space station that served as a long-term research outpost in low Earth orbit from 1986 to 2001.
  • E. Marg
    Marg is a given name, typically a shortened form of Margaret, used primarily in English-speaking contexts.
  • 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_69ca82eea2b88190a0e511d21a31f386 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdb84b47308190aa2f94fa7320cdc3 completed April 2, 2026, 12:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69d23de601f0819096004bf60ffa2d2c completed April 5, 2026, 10:48 a.m.
NEDg Description generation batch_69d241e666a0819087061bf8af397131 completed April 5, 2026, 11:05 a.m.
NED2 Entity disambiguation (via description) batch_69d24283caa481908d794ea2cd4f9db3 completed April 5, 2026, 11:07 a.m.
Created at: March 30, 2026, 8:48 p.m.