Triple

T2262806
Position Surface form Disambiguated ID Type / Status
Subject TAR Aerolíneas E50075 entity
Predicate callsign P1565 FINISHED
Object TAR
TAR is a Mexican regional airline operating domestic passenger flights to various destinations across the country.
 E251768 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: TAR | Statement: [TAR Aerolíneas, callsign, TAR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TAR
Context triple: [TAR Aerolíneas, callsign, TAR]
  • A. TAR
    TAR is the ICAO airline designator assigned to Tunisair, the national flag carrier of Tunisia.
  • B. TAR
    TAR is the commonly used abbreviation for the Intergovernmental Panel on Climate Change’s Third Assessment Report on climate change.
  • C. ATA
    ATA is the acronym for the Allen Telescope Array, a large-scale radio telescope array in California designed for astronomical observations and the search for extraterrestrial intelligence.
  • D. ATA
    ATA (Advanced Technology Attachment), commonly known as IDE, is a standard interface used to connect storage devices like hard drives and optical drives to a computer's motherboard.
  • E. TARS
    TARS is a witty, modular, and highly capable robotic assistant featured in the science fiction film "Interstellar."
  • 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: TAR
Triple: [TAR Aerolíneas, callsign, TAR]
Generated description
TAR is a Mexican regional airline operating domestic passenger flights to various destinations across the country.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TAR
Target entity description: TAR is a Mexican regional airline operating domestic passenger flights to various destinations across the country.
  • A. TAR
    TAR is the ICAO airline designator assigned to Tunisair, the national flag carrier of Tunisia.
  • B. TAR
    TAR is the commonly used abbreviation for the Intergovernmental Panel on Climate Change’s Third Assessment Report on climate change.
  • C. ATA
    ATA (Advanced Technology Attachment), commonly known as IDE, is a standard interface used to connect storage devices like hard drives and optical drives to a computer's motherboard.
  • D. ATA
    ATA is the acronym for the Allen Telescope Array, a large-scale radio telescope array in California designed for astronomical observations and the search for extraterrestrial intelligence.
  • E. TARS
    TARS is a witty, modular, and highly capable robotic assistant featured in the science fiction film "Interstellar."
  • 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_69a88b01e0048190ba96431b5f990ba9 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abc18be8308190abc4a59d37dfd93a completed March 7, 2026, 6:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae71cfd3b08190988474aa0fa985fe completed March 9, 2026, 7:08 a.m.
NEDg Description generation batch_69ae7688583c8190abb05be41103762a completed March 9, 2026, 7:28 a.m.
NED2 Entity disambiguation (via description) batch_69ae76ec3c0c8190bfb7d25b435c777f completed March 9, 2026, 7:29 a.m.
Created at: March 4, 2026, 7:48 p.m.