Triple

T3149803
Position Surface form Disambiguated ID Type / Status
Subject Big Ten Network E65849 entity
Predicate formerName P65 FINISHED
Object BTN
BTN is a U.S. sports television network dedicated primarily to broadcasting collegiate athletics and related programming from the Big Ten Conference.
 E331322 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: BTN | Statement: [Big Ten Network, formerName, BTN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: BTN
Context triple: [Big Ten Network, formerName, BTN]
  • A. BTN
    BTN is the three-letter ISO 3166-1 alpha-3 country code assigned to Bhutan.
  • B. BN
    BN is the vehicle registration code used on license plates for the German city of Bonn.
  • C. BAT
    BAT is a major multinational tobacco company known for producing and marketing cigarettes and other nicotine products worldwide.
  • D. Bt
    Bt is the post-nominal abbreviation for a baronetcy title in the British honours system, indicating that the holder is a baronet.
  • E. BEN
    BEN is the three-letter IATA airport code assigned to Benina International Airport serving Benghazi, Libya.
  • 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: BTN
Triple: [Big Ten Network, formerName, BTN]
Generated description
BTN is a U.S. sports television network dedicated primarily to broadcasting collegiate athletics and related programming from the Big Ten Conference.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: BTN
Target entity description: BTN is a U.S. sports television network dedicated primarily to broadcasting collegiate athletics and related programming from the Big Ten Conference.
  • A. BTN
    BTN is the three-letter ISO 3166-1 alpha-3 country code assigned to Bhutan.
  • B. BN
    BN is the vehicle registration code used on license plates for the German city of Bonn.
  • C. BAT
    BAT is a major multinational tobacco company known for producing and marketing cigarettes and other nicotine products worldwide.
  • D. Bt
    Bt is the post-nominal abbreviation for a baronetcy title in the British honours system, indicating that the holder is a baronet.
  • E. BEN
    BEN is the three-letter IATA airport code assigned to Benina International Airport serving Benghazi, Libya.
  • 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_69ad8584485081909ed529e890cadc4a completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada5bf902c8190a490fa55e2dcecc0 completed March 8, 2026, 4:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69b224f94f3881909a277c45c9add0f5 completed March 12, 2026, 2:29 a.m.
NEDg Description generation batch_69b225b27e1c8190a3df0d4692ee66c6 completed March 12, 2026, 2:32 a.m.
NED2 Entity disambiguation (via description) batch_69b226339e4881908690f7ea7a7bd50c completed March 12, 2026, 2:34 a.m.
Created at: March 8, 2026, 3:05 p.m.