Triple

T7759152
Position Surface form Disambiguated ID Type / Status
Subject Toledo Express Airport E175973 entity
Predicate IATAcode P418 FINISHED
Object TOL
TOL is the IATA airport code for Toledo Express Airport, a public airport serving the Toledo, Ohio area in the United States.
E687019 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: TOL | Statement: [Toledo Express Airport, IATAcode, TOL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TOL
Context triple: [Toledo Express Airport, IATAcode, TOL]
  • A. TOL
    TOL is the standard abbreviation for the Toledo Walleye, a professional minor league ice hockey team based in Toledo, Ohio.
  • B. TLO
    TLO, also known as Dario Wünsch, is a German professional StarCraft II player renowned for his creative strategies and long-standing presence in the competitive scene.
  • C. Toller
    Toller is a supporting character in the 1966 Western film "Duel at Diablo," set against the backdrop of frontier conflict between U.S. cavalry and Apache forces.
  • D. CO-TOL
    CO-TOL is the ISO 3166-2 code that uniquely identifies Colombia’s Tolima Department in international and administrative contexts.
  • E. Tololing
    Tololing is a strategically important mountain peak in the Dras sector of Kargil, Jammu and Kashmir, that was the site of intense fighting during the 1999 Kargil War between India and Pakistan.
  • 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: TOL
Triple: [Toledo Express Airport, IATAcode, TOL]
Generated description
TOL is the IATA airport code for Toledo Express Airport, a public airport serving the Toledo, Ohio area in the United States.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: TOL
Target entity description: TOL is the IATA airport code for Toledo Express Airport, a public airport serving the Toledo, Ohio area in the United States.
  • A. TOL
    TOL is the standard abbreviation for the Toledo Walleye, a professional minor league ice hockey team based in Toledo, Ohio.
  • B. TLO
    TLO, also known as Dario Wünsch, is a German professional StarCraft II player renowned for his creative strategies and long-standing presence in the competitive scene.
  • C. Toller
    Toller is a supporting character in the 1966 Western film "Duel at Diablo," set against the backdrop of frontier conflict between U.S. cavalry and Apache forces.
  • D. CO-TOL
    CO-TOL is the ISO 3166-2 code that uniquely identifies Colombia’s Tolima Department in international and administrative contexts.
  • E. Tololing
    Tololing is a strategically important mountain peak in the Dras sector of Kargil, Jammu and Kashmir, that was the site of intense fighting during the 1999 Kargil War between India and Pakistan.
  • 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_69c6996180088190832e38e8d83ff54a completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c703de43d08190ac28bc17cd3e5ffa completed March 27, 2026, 10:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8c7cf538c8190aa86c27fff42efb0 completed March 29, 2026, 6:33 a.m.
NEDg Description generation batch_69c8c8a18860819081a88f80544db83d completed March 29, 2026, 6:37 a.m.
NED2 Entity disambiguation (via description) batch_69c8c900a28c819097449e8ceb373718 completed March 29, 2026, 6:38 a.m.
Created at: March 27, 2026, 4:09 p.m.