Triple

T12434534
Position Surface form Disambiguated ID Type / Status
Subject Stade Roland Garros E297110 entity
Predicate namedAfter P63 FINISHED
Object Roland Garros
Roland Garros was a pioneering French aviator and World War I fighter pilot, best known for his early long-distance flights and for helping develop forward-firing machine guns on aircraft.
 E980628 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: Roland Garros | Statement: [Stade Roland Garros, namedAfter, Roland Garros]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Roland Garros
Context triple: [Stade Roland Garros, namedAfter, Roland Garros]
  • A. Stade Roland Garros
    Stade Roland Garros is a famous Parisian tennis complex best known as the venue for the French Open, one of the four Grand Slam tournaments.
  • B. Tournefeuille
    Tournefeuille is a suburban town in southwestern France, located near Toulouse in the Occitanie region.
  • C. French Open
    The French Open is one of tennis's four major Grand Slam tournaments, renowned for its clay courts and held annually at Roland Garros in Paris.
  • D. Parc des Princes
    Parc des Princes is a major football stadium in Paris, best known as the historic home ground of Paris Saint-Germain (PSG).
  • E. Billancourt
    Billancourt is a Paris Métro station in Boulogne-Billancourt serving the western suburbs of the French capital.
  • 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: Roland Garros
Triple: [Stade Roland Garros, namedAfter, Roland Garros]
Generated description
Roland Garros was a pioneering French aviator and World War I fighter pilot, best known for his early long-distance flights and for helping develop forward-firing machine guns on aircraft.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Roland Garros
Target entity description: Roland Garros was a pioneering French aviator and World War I fighter pilot, best known for his early long-distance flights and for helping develop forward-firing machine guns on aircraft.
  • A. Stade Roland Garros
    Stade Roland Garros is a famous Parisian tennis complex best known as the venue for the French Open, one of the four Grand Slam tournaments.
  • B. Tournefeuille
    Tournefeuille is a suburban town in southwestern France, located near Toulouse in the Occitanie region.
  • C. French Open
    The French Open is one of tennis's four major Grand Slam tournaments, renowned for its clay courts and held annually at Roland Garros in Paris.
  • D. Parc des Princes
    Parc des Princes is a major football stadium in Paris, best known as the historic home ground of Paris Saint-Germain (PSG).
  • E. Billancourt
    Billancourt is a Paris Métro station in Boulogne-Billancourt serving the western suburbs of the French capital.
  • 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_69d6ada0640c81908c061d7fb3d47786 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94d804c2c819082f2f86edcbb50de completed April 10, 2026, 7:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6349f0f34819080e7d7f83f7baece completed May 2, 2026, 5:30 p.m.
NEDg Description generation batch_69f6359a52b4819096c3f520a5714b0a completed May 2, 2026, 5:34 p.m.
NED2 Entity disambiguation (via description) batch_69f63693f5c881909a9683a0c6a68739 completed May 2, 2026, 5:38 p.m.
Created at: April 8, 2026, 9:55 p.m.