Triple

T828973
Position Surface form Disambiguated ID Type / Status
Subject Tunisair E17920 entity
Predicate callsign P1565 FINISHED
Object TUNAIR
TUNAIR is the radio callsign used by Tunisair, the national flag carrier airline of Tunisia.
 E96506 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: TUNAIR | Statement: [Tunisair, callsign, TUNAIR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TUNAIR
Context triple: [Tunisair, callsign, TUNAIR]
  • A. TUN
    TUN is the three-letter ISO 3166-1 alpha-3 country code assigned to Tunisia.
  • B. Philortyx
    Philortyx is a genus of New World quails known for their ground-dwelling habits and occurrence in scrub and grassland habitats of the Americas.
  • C. Ramport Aero
    Ramport Aero is the company responsible for managing and operating Zhukovsky International Airport near Moscow, Russia.
  • D. TNUA
    TNUA is an academic association or network that includes Nagoya University among its member institutions.
  • E. Tikkana
    Tikkana was a prominent 13th-century Telugu poet and scholar best known for translating a major portion of the Mahabharata into Telugu and helping shape classical Telugu 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: TUNAIR
Triple: [Tunisair, callsign, TUNAIR]
Generated description
TUNAIR is the radio callsign used by Tunisair, the national flag carrier airline of Tunisia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TUNAIR
Target entity description: TUNAIR is the radio callsign used by Tunisair, the national flag carrier airline of Tunisia.
  • A. TUN
    TUN is the three-letter ISO 3166-1 alpha-3 country code assigned to Tunisia.
  • B. Philortyx
    Philortyx is a genus of New World quails known for their ground-dwelling habits and occurrence in scrub and grassland habitats of the Americas.
  • C. Ramport Aero
    Ramport Aero is the company responsible for managing and operating Zhukovsky International Airport near Moscow, Russia.
  • D. TNUA
    TNUA is an academic association or network that includes Nagoya University among its member institutions.
  • E. Tikkana
    Tikkana was a prominent 13th-century Telugu poet and scholar best known for translating a major portion of the Mahabharata into Telugu and helping shape classical Telugu 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_69a4937c9c188190aaa216f6b466f452 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4ab9b458881909aa23f0eb7cbc87f completed March 1, 2026, 9:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69a76d97a3b08190b7a5c635d74bcd47 completed March 3, 2026, 11:24 p.m.
NEDg Description generation batch_69a783814b188190b449cd191667f1a1 completed March 4, 2026, 12:57 a.m.
NED2 Entity disambiguation (via description) batch_69a7840593988190b6882b456f0eea41 completed March 4, 2026, 12:59 a.m.
Created at: March 1, 2026, 7:38 p.m.