Triple

T3716939
Position Surface form Disambiguated ID Type / Status
Subject FTSE MIB E81552 entity
Predicate hasTickerSymbol P1447 FINISHED
Object FTSEMIB
FTSEMIB is the ticker symbol for Italy’s primary stock market index, which tracks the performance of the 40 most liquid and capitalized companies listed on the Borsa Italiana.
 E381945 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: FTSEMIB | Statement: [FTSE MIB, hasTickerSymbol, FTSEMIB]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: FTSEMIB
Context triple: [FTSE MIB, hasTickerSymbol, FTSEMIB]
  • A. ITM
    ITM is the IATA airport code for Osaka International Airport, a major domestic airport serving the Osaka metropolitan area in Japan.
  • B. NMTI
    NMTI is a prestigious United States presidential award that honors individuals, teams, and companies for outstanding contributions to technological innovation and advancement.
  • C. NMTI
    NMTI is an acronym whose specific meaning depends on context, commonly referring to various technical or institutional names.
  • D. SIF
    SIF is the governing body for ice hockey in Sweden, overseeing the national teams and domestic competitions.
  • E. SMF
    SMF (System Management Facilities) is an IBM z/OS component that collects and records system and workload performance data for monitoring, accounting, and capacity planning.
  • 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: FTSEMIB
Triple: [FTSE MIB, hasTickerSymbol, FTSEMIB]
Generated description
FTSEMIB is the ticker symbol for Italy’s primary stock market index, which tracks the performance of the 40 most liquid and capitalized companies listed on the Borsa Italiana.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: FTSEMIB
Target entity description: FTSEMIB is the ticker symbol for Italy’s primary stock market index, which tracks the performance of the 40 most liquid and capitalized companies listed on the Borsa Italiana.
  • A. ITM
    ITM is the IATA airport code for Osaka International Airport, a major domestic airport serving the Osaka metropolitan area in Japan.
  • B. NMTI
    NMTI is a prestigious United States presidential award that honors individuals, teams, and companies for outstanding contributions to technological innovation and advancement.
  • C. NMTI
    NMTI is an acronym whose specific meaning depends on context, commonly referring to various technical or institutional names.
  • D. SIF
    SIF is the governing body for ice hockey in Sweden, overseeing the national teams and domestic competitions.
  • E. SMF
    SMF is the three-letter IATA airport code for Sacramento International Airport, the primary commercial airport serving California’s capital city.
  • 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_69ad8b1a81588190b3f27a5483bb610e completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adc9d087c881909f6d2ec6e518fb02 completed March 8, 2026, 7:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4ce1260948190b4707337e9427c2c completed March 14, 2026, 2:55 a.m.
NEDg Description generation batch_69b4cf799ae88190bbf821f4c4500031 completed March 14, 2026, 3:01 a.m.
NED2 Entity disambiguation (via description) batch_69b4d0057fe8819092a40732324f88c9 completed March 14, 2026, 3:03 a.m.
Created at: March 8, 2026, 3:33 p.m.