Triple

T15831725
Position Surface form Disambiguated ID Type / Status
Subject Terreaux quarter E383886 entity
Predicate hasPart P35 FINISHED
Object Place Louis Pradel
Place Louis Pradel is a central public square in Lyon, France, known for its modern urban design and proximity to major cultural institutions and transport hubs.
E1179060 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: Place Louis Pradel | Statement: [Terreaux quarter, hasPart, Place Louis Pradel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Place Louis Pradel
Context triple: [Terreaux quarter, hasPart, Place Louis Pradel]
  • A. Patrick Baudry
    Patrick Baudry is a French astronaut and test pilot who became one of the first French citizens to fly in space.
  • B. Frédéric Bricout
    Frédéric Bricout is a French politician who serves as the mayor of the northern French city of Cambrai.
  • C. André Dussollier
    André Dussollier is a renowned French actor known for his versatile performances in film, television, and theater since the 1970s.
  • D. Stéphane Loda
    Stéphane Loda is a French local politician who serves as the mayor of the Mediterranean coastal commune of Canet-en-Roussillon.
  • E. Jérôme Lindon
    Jérôme Lindon was a prominent French publisher best known for directing Éditions de Minuit and championing avant-garde and politically engaged literature.
  • 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: Place Louis Pradel
Triple: [Terreaux quarter, hasPart, Place Louis Pradel]
Generated description
Place Louis Pradel is a central public square in Lyon, France, known for its modern urban design and proximity to major cultural institutions and transport hubs.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Place Louis Pradel
Target entity description: Place Louis Pradel is a central public square in Lyon, France, known for its modern urban design and proximity to major cultural institutions and transport hubs.
  • A. Patrick Baudry
    Patrick Baudry is a French astronaut and test pilot who became one of the first French citizens to fly in space.
  • B. Frédéric Bricout
    Frédéric Bricout is a French politician who serves as the mayor of the northern French city of Cambrai.
  • C. André Dussollier
    André Dussollier is a renowned French actor known for his versatile performances in film, television, and theater since the 1970s.
  • D. Stéphane Loda
    Stéphane Loda is a French local politician who serves as the mayor of the Mediterranean coastal commune of Canet-en-Roussillon.
  • E. Jérôme Lindon
    Jérôme Lindon was a prominent French publisher best known for directing Éditions de Minuit and championing avant-garde and politically engaged literature.
  • 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_69d86da34c888190976e06c4019d415a completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e11e6433ac8190a3d3e0d573673ea3 completed April 16, 2026, 5:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff999f9ccc8190bc859c2b78a16baf completed May 9, 2026, 8:31 p.m.
NEDg Description generation batch_69ff9bf7363c8190a65798028305b1da completed May 9, 2026, 8:41 p.m.
NED2 Entity disambiguation (via description) batch_69ff9c580d608190a7b3de11a924cba7 completed May 9, 2026, 8:43 p.m.
Created at: April 10, 2026, 4:49 a.m.