Triple

T18875949
Position Surface form Disambiguated ID Type / Status
Subject Tony Musante E461685 entity
Predicate televisionSeries P3279 FINISHED
Object Toma
Toma is a 1970s American crime drama television series starring Tony Musante as a maverick undercover detective.
E1348959 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: Toma | Statement: [Tony Musante, televisionSeries, Toma]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Toma
Context triple: [Tony Musante, televisionSeries, Toma]
  • A. Toma
    Toma is a traditional semi-hard cow’s milk cheese from Italy’s Piedmont region, known for its mild, buttery flavor and smooth, elastic texture.
  • B. Toma
    Toma is a small town located in Kamikawa Subprefecture on Japan’s northern island of Hokkaido.
  • C. Toma
    Toma is a masculine given name used in various European cultures, often as a form of Thomas.
  • D. Toma
    Toma is a major Mande language spoken primarily in Guinea and neighboring West African countries.
  • E. Saca
    Saca is a Spanish-language surname most notably associated with former Salvadoran president Antonio Saca.
  • 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: Toma
Triple: [Tony Musante, televisionSeries, Toma]
Generated description
Toma is a 1970s American crime drama television series starring Tony Musante as a maverick undercover detective.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Toma
Target entity description: Toma is a 1970s American crime drama television series starring Tony Musante as a maverick undercover detective.
  • A. Toma
    Toma is a major Mande language spoken primarily in Guinea and neighboring West African countries.
  • B. Toma
    Toma is a traditional semi-hard cow’s milk cheese from Italy’s Piedmont region, known for its mild, buttery flavor and smooth, elastic texture.
  • C. Toma
    Toma is a small town located in Kamikawa Subprefecture on Japan’s northern island of Hokkaido.
  • D. Toma
    Toma is a masculine given name used in various European cultures, often as a form of Thomas.
  • E. Saca
    Saca is a Spanish-language surname most notably associated with former Salvadoran president Antonio Saca.
  • 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_69d8dcfc3430819095ee6fc0eb4c06a5 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5c3ce07788190a179705eb1b6c824 completed April 20, 2026, 6:12 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0582acb67c819080c5553167a22db0 completed May 14, 2026, 8:07 a.m.
NEDg Description generation batch_6a05887693d081908fa60534c3c36144 completed May 14, 2026, 8:31 a.m.
NED2 Entity disambiguation (via description) batch_6a05891f4a248190a5527a939fcb16da completed May 14, 2026, 8:34 a.m.
Created at: April 10, 2026, 11:57 a.m.