Triple

T12293774
Position Surface form Disambiguated ID Type / Status
Subject Tupolev Tu-154 E293031 entity
Predicate icaoDesignator P16898 FINISHED
Object T154
T154 is the ICAO aircraft type designator for the Soviet-designed Tupolev Tu-154, a three‑engine medium‑range narrow‑body airliner widely used by Eastern Bloc and Russian airlines.
 E975268 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: T154 | Statement: [Tupolev Tu-154, icaoDesignator, T154]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: T154
Context triple: [Tupolev Tu-154, icaoDesignator, T154]
  • A. T134
    T134 is the ICAO aircraft type designator assigned to the Soviet-era twin-engine jet airliner Tupolev Tu-134.
  • B. T11
    T11 is the FAA location identifier assigned to Yap International Airport in the Federated States of Micronesia.
  • C. TAF15
    TAF15 is an RNA-binding protein and transcription factor associated with gene regulation and implicated in certain cancers and neurodegenerative diseases.
  • D. T4
    T4 is the large, modern main passenger terminal at Adolfo Suárez Madrid–Barajas Airport in Madrid, Spain, known for its distinctive architecture and extensive international flight operations.
  • E. T4
    T4 is the fourth passenger terminal at Melbourne Airport, serving as one of the airport’s main facilities for domestic and low-cost airline operations.
  • 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: T154
Triple: [Tupolev Tu-154, icaoDesignator, T154]
Generated description
T154 is the ICAO aircraft type designator for the Soviet-designed Tupolev Tu-154, a three‑engine medium‑range narrow‑body airliner widely used by Eastern Bloc and Russian airlines.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: T154
Target entity description: T154 is the ICAO aircraft type designator for the Soviet-designed Tupolev Tu-154, a three‑engine medium‑range narrow‑body airliner widely used by Eastern Bloc and Russian airlines.
  • A. T134
    T134 is the ICAO aircraft type designator assigned to the Soviet-era twin-engine jet airliner Tupolev Tu-134.
  • B. T11
    T11 is the FAA location identifier assigned to Yap International Airport in the Federated States of Micronesia.
  • C. TAF15
    TAF15 is an RNA-binding protein and transcription factor associated with gene regulation and implicated in certain cancers and neurodegenerative diseases.
  • D. T4
    T4 is the large, modern main passenger terminal at Adolfo Suárez Madrid–Barajas Airport in Madrid, Spain, known for its distinctive architecture and extensive international flight operations.
  • E. T4
    T4 is the fourth passenger terminal at Melbourne Airport, serving as one of the airport’s main facilities for domestic and low-cost airline operations.
  • 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_69d6ab690ad081908c0ed3870ec82d53 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91d23def88190adbaa282dd03d6c6 completed April 10, 2026, 3:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69f61e79bf548190bf7f314222ed1ed1 completed May 2, 2026, 3:55 p.m.
NEDg Description generation batch_69f62260d6708190808e52935a27e2c1 completed May 2, 2026, 4:12 p.m.
NED2 Entity disambiguation (via description) batch_69f6230f4c8081908a759efa43b4800b completed May 2, 2026, 4:15 p.m.
Created at: April 8, 2026, 9:52 p.m.