Triple

T717365
Position Surface form Disambiguated ID Type / Status
Subject Occitanie E14341 entity
Predicate containsCity P294 FINISHED
Object Lot
Lot is a department in southwestern France known for its picturesque river valleys, medieval villages, and prehistoric cave art.
E85346 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: Lot | Statement: [Occitanie, containsCity, Lot]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lot
Context triple: [Occitanie, containsCity, Lot]
  • A. Lot
    Lot is a river in southwestern France known for flowing through scenic valleys and historic towns before joining the Garonne.
  • B. Land
    Land Morrow Lindbergh is the son of aviator Charles Lindbergh and writer Anne Morrow Lindbergh.
  • C. Backlot
    Backlot is a program at the Telluride Film Festival dedicated to films about cinema, featuring documentaries and works that explore filmmakers, film history, and the moviemaking process.
  • D. Settle
    Settle is a small market town in North Yorkshire, England, known as a gateway to the Yorkshire Dales and the scenic Settle–Carlisle railway.
  • E. To Let
    "To Let" is a 1921 novel by John Galsworthy that serves as the final installment of his acclaimed Forsyte Saga, chronicling the decline and transformation of the upper-middle-class Forsyte family.
  • 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: Lot
Triple: [Occitanie, containsCity, Lot]
Generated description
Lot is a department in southwestern France known for its picturesque river valleys, medieval villages, and prehistoric cave art.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Lot
Target entity description: Lot is a department in southwestern France known for its picturesque river valleys, medieval villages, and prehistoric cave art.
  • A. Lot
    Lot is a river in southwestern France known for flowing through scenic valleys and historic towns before joining the Garonne.
  • B. Land
    Land Morrow Lindbergh is the son of aviator Charles Lindbergh and writer Anne Morrow Lindbergh.
  • C. Backlot
    Backlot is a program at the Telluride Film Festival dedicated to films about cinema, featuring documentaries and works that explore filmmakers, film history, and the moviemaking process.
  • D. Settle
    Settle is a small market town in North Yorkshire, England, known as a gateway to the Yorkshire Dales and the scenic Settle–Carlisle railway.
  • E. To Let
    "To Let" is a 1921 novel by John Galsworthy that serves as the final installment of his acclaimed Forsyte Saga, chronicling the decline and transformation of the upper-middle-class Forsyte family.
  • 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_69a4934a36e081909e7abef98b898a4e completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a577658881909c12951d63d96377 completed March 1, 2026, 8:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5dcb77bc481909d79542001fafbd2 completed March 2, 2026, 6:53 p.m.
NEDg Description generation batch_69a5de57bbec81908a5d1202299194f4 completed March 2, 2026, 7 p.m.
NED2 Entity disambiguation (via description) batch_69a60952c6388190a23a178d695eec6e completed March 2, 2026, 10:04 p.m.
Created at: March 1, 2026, 7:37 p.m.