Triple

T9219040
Position Surface form Disambiguated ID Type / Status
Subject Paris–Cherbourg railway E221312 entity
Predicate passesThrough P225 FINISHED
Object Lison
Lison is a small commune in the Calvados department of Normandy in northwestern France.
 E785436 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: Lison | Statement: [Paris–Cherbourg railway, passesThrough, Lison]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lison
Context triple: [Paris–Cherbourg railway, passesThrough, Lison]
  • A. Delarue
    Delarue is a vengeful ex-soldier and gunslinger who serves as the main protagonist in the Western thriller film "The Salvation."
  • B. Lusser
    Lusser is a German surname most notably associated with engineer Robert Lusser, known for his contributions to aeronautics and reliability engineering.
  • C. Greuze
    Greuze is a French surname most famously associated with Jean-Baptiste Greuze, an 18th-century painter known for his sentimental and moralizing genre scenes.
  • D. Barbaroux
    Barbaroux is a French surname most notably associated with Charles Barbaroux, a prominent figure of the French Revolution.
  • E. Sylvain
    Sylvain is a masculine given name of French origin commonly used in Francophone countries.
  • 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: Lison
Triple: [Paris–Cherbourg railway, passesThrough, Lison]
Generated description
Lison is a small commune in the Calvados department of Normandy in northwestern France.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lison
Target entity description: Lison is a small commune in the Calvados department of Normandy in northwestern France.
  • A. Delarue
    Delarue is a vengeful ex-soldier and gunslinger who serves as the main protagonist in the Western thriller film "The Salvation."
  • B. Lusser
    Lusser is a German surname most notably associated with engineer Robert Lusser, known for his contributions to aeronautics and reliability engineering.
  • C. Greuze
    Greuze is a French surname most famously associated with Jean-Baptiste Greuze, an 18th-century painter known for his sentimental and moralizing genre scenes.
  • D. Barbaroux
    Barbaroux is a French surname most notably associated with Charles Barbaroux, a prominent figure of the French Revolution.
  • E. Sylvain
    Sylvain is a masculine given name of French origin commonly used in Francophone countries.
  • 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_69ca83eae42c8190a0ea9e040710a277 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccda730f688190b64b2cc8c4898ac3 completed April 1, 2026, 8:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69d0662c28648190979cf786fc35ab75 completed April 4, 2026, 1:15 a.m.
NEDg Description generation batch_69d06770ccf08190b00bf35c16a80071 completed April 4, 2026, 1:20 a.m.
NED2 Entity disambiguation (via description) batch_69d06864b8c48190b8e08ab9c1c85c9a completed April 4, 2026, 1:24 a.m.
Created at: March 30, 2026, 7:27 p.m.