Triple

T4320750
Position Surface form Disambiguated ID Type / Status
Subject Bourse de Tunis E96508 entity
Predicate hasIndex P2915 FINISHED
Object Tunindex 20
Tunindex 20 is a benchmark stock market index comprising the 20 most actively traded and capitalized companies listed on the Tunis Stock Exchange.
E432205 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: Tunindex 20 | Statement: [Bourse de Tunis, hasIndex, Tunindex 20]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tunindex 20
Context triple: [Bourse de Tunis, hasIndex, Tunindex 20]
  • A. TUNAIR
    TUNAIR is the radio callsign used by Tunisair, the national flag carrier airline of Tunisia.
  • B. Tunechi
    Tunechi is a popular nickname and alter ego of American rapper Lil Wayne, often used to refer to his distinctive persona and musical brand.
  • C. In Tune
    In Tune is a long-running BBC Radio 3 magazine programme featuring live classical music performances, interviews with musicians, and arts news.
  • D. T2
    T2 is San Francisco International Airport’s Terminal 2, a modern passenger terminal serving domestic flights with updated amenities and design.
  • E. T2
    T2 is a passenger terminal at Berlin Brandenburg Airport that handles check-in, security, and boarding operations for departing and arriving travelers.
  • 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: Tunindex 20
Triple: [Bourse de Tunis, hasIndex, Tunindex 20]
Generated description
Tunindex 20 is a benchmark stock market index comprising the 20 most actively traded and capitalized companies listed on the Tunis Stock Exchange.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tunindex 20
Target entity description: Tunindex 20 is a benchmark stock market index comprising the 20 most actively traded and capitalized companies listed on the Tunis Stock Exchange.
  • A. TUNAIR
    TUNAIR is the radio callsign used by Tunisair, the national flag carrier airline of Tunisia.
  • B. Tunechi
    Tunechi is a popular nickname and alter ego of American rapper Lil Wayne, often used to refer to his distinctive persona and musical brand.
  • C. In Tune
    In Tune is a long-running BBC Radio 3 magazine programme featuring live classical music performances, interviews with musicians, and arts news.
  • D. T2
    T2 is a shorthand title for the 1991 science fiction action film "Terminator 2: Judgment Day," directed by James Cameron and starring Arnold Schwarzenegger.
  • E. T2
    T2 is San Francisco International Airport’s Terminal 2, a modern passenger terminal serving domestic flights with updated amenities and design.
  • 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_69b345422aac81909ddbadae437d122e completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b35114ed2c8190949c5d8032d7b921 completed March 12, 2026, 11:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5d08d70408190aca5793a480cf54f completed March 14, 2026, 9:18 p.m.
NEDg Description generation batch_69b5d4607a688190a3a7352579ea5ee7 completed March 14, 2026, 9:34 p.m.
NED2 Entity disambiguation (via description) batch_69b5d51068dc819099ac28361188dcc4 completed March 14, 2026, 9:37 p.m.
Created at: March 12, 2026, 11:12 p.m.