Triple

T8721736
Position Surface form Disambiguated ID Type / Status
Subject MAS Saint-Étienne E207026 entity
Predicate shortName P43 FINISHED
Object MAS
MAS is a sports club based in Saint-Étienne, France, known for its participation in regional football competitions.
 E752857 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: MAS | Statement: [MAS Saint-Étienne, shortName, MAS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MAS
Context triple: [MAS Saint-Étienne, shortName, MAS]
  • A. MAS
    MAS is the ICAO airline designator used to identify Malaysia Airlines in international aviation operations.
  • B. MAS
    MAS (Monetary Authority of Singapore) is Singapore’s central bank and integrated financial regulator, responsible for monetary policy, financial supervision, and the stability of the country’s financial system.
  • C. MAS
    MAS is the official Indian Railways station code for Chennai Central, one of the busiest and most important railway terminals in South India.
  • D. MASI
    MASI is the main all-share stock market index of the Casablanca Stock Exchange in Morocco, tracking the performance of its listed companies.
  • E. MASP
    MASP (Museu de Arte de São Paulo) is one of Brazil’s most important art museums, renowned for its striking modernist architecture and extensive collection of Western and Brazilian art.
  • 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: MAS
Triple: [MAS Saint-Étienne, shortName, MAS]
Generated description
MAS is a sports club based in Saint-Étienne, France, known for its participation in regional football competitions.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MAS
Target entity description: MAS is a sports club based in Saint-Étienne, France, known for its participation in regional football competitions.
  • A. MAS
    MAS is the ICAO airline designator used to identify Malaysia Airlines in international aviation operations.
  • B. MAS
    MAS (Monetary Authority of Singapore) is Singapore’s central bank and integrated financial regulator, responsible for monetary policy, financial supervision, and the stability of the country’s financial system.
  • C. MAS
    MAS is the official Indian Railways station code for Chennai Central, one of the busiest and most important railway terminals in South India.
  • D. MASI
    MASI is the main all-share stock market index of the Casablanca Stock Exchange in Morocco, tracking the performance of its listed companies.
  • E. MASP
    MASP (Museu de Arte de São Paulo) is one of Brazil’s most important art museums, renowned for its striking modernist architecture and extensive collection of Western and Brazilian art.
  • 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_69ca835811d8819081ea00fd2a2c9a1c completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5d03f0848190a50c77e5cd028ee7 completed March 31, 2026, 11:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf28f599a481908e93bc5b5c41296e completed April 3, 2026, 2:41 a.m.
NEDg Description generation batch_69cf2bd32cc881909ac8a61befa9929e completed April 3, 2026, 2:54 a.m.
NED2 Entity disambiguation (via description) batch_69cf2c69f83481909423858668d03a8b completed April 3, 2026, 2:56 a.m.
Created at: March 30, 2026, 6:36 p.m.