Triple

T12183143
Position Surface form Disambiguated ID Type / Status
Subject Children's Television Workshop E290268 entity
Predicate alsoKnownAs P39 FINISHED
Object CTW
CTW, short for Children's Television Workshop, is the American nonprofit organization best known for creating the educational children's television series "Sesame Street."
 E968394 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: CTW | Statement: [Children's Television Workshop, alsoKnownAs, CTW]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: CTW
Context triple: [Children's Television Workshop, alsoKnownAs, CTW]
  • A. CTW
    CTW is the IATA airport code for Cottonwood Municipal Airport, a public airport serving the city of Cottonwood, Arizona.
  • B. TTW
    TTW is the ICAO airline designator assigned to Tigerair Taiwan, a low-cost carrier based in Taiwan.
  • C. CTSFW
    CTSFW is the commonly used abbreviation for Concordia Theological Seminary in Fort Wayne, a Lutheran seminary that trains pastors and church workers.
  • D. CTN
    CTN is the ICAO airline designator used to identify Croatia Airlines in international aviation operations.
  • E. GTW
    GTW was the stock ticker symbol for Gateway, Inc., a former major American personal computer manufacturer known for its cow-spotted boxes and direct-to-consumer sales model.
  • 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: CTW
Triple: [Children's Television Workshop, alsoKnownAs, CTW]
Generated description
CTW, short for Children's Television Workshop, is the American nonprofit organization best known for creating the educational children's television series "Sesame Street."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: CTW
Target entity description: CTW, short for Children's Television Workshop, is the American nonprofit organization best known for creating the educational children's television series "Sesame Street."
  • A. CTW
    CTW is the IATA airport code for Cottonwood Municipal Airport, a public airport serving the city of Cottonwood, Arizona.
  • B. TTW
    TTW is the ICAO airline designator assigned to Tigerair Taiwan, a low-cost carrier based in Taiwan.
  • C. CTSFW
    CTSFW is the commonly used abbreviation for Concordia Theological Seminary in Fort Wayne, a Lutheran seminary that trains pastors and church workers.
  • D. CTN
    CTN is the ICAO airline designator used to identify Croatia Airlines in international aviation operations.
  • E. GTW
    GTW was the stock ticker symbol for Gateway, Inc., a former major American personal computer manufacturer known for its cow-spotted boxes and direct-to-consumer sales model.
  • 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_69d6ab64de5881908d56eb7a75c6cc69 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d915fd8dac8190928059ad2b6bbbf3 completed April 10, 2026, 3:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f6acee6481908ee4129956c98c52 completed May 2, 2026, 1:05 p.m.
NEDg Description generation batch_69f6022ecf38819080f0eb6a3a815c5b completed May 2, 2026, 1:54 p.m.
NED2 Entity disambiguation (via description) batch_69f606560934819092ba4d4fa162b799 completed May 2, 2026, 2:12 p.m.
Created at: April 8, 2026, 9:50 p.m.