Triple

T17940836
Position Surface form Disambiguated ID Type / Status
Subject Toma Erdődy E448580 entity
Predicate givenName P17 FINISHED
Object Toma
Toma is a masculine given name used in various European cultures, often as a form of Thomas.
 E1297989 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: [Toma Erdődy, givenName, Toma]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Toma
Context triple: [Toma Erdődy, givenName, 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 major Mande language spoken primarily in Guinea and neighboring West African countries.
  • C. Toma
    Toma is a small town located in Kamikawa Subprefecture on Japan’s northern island of Hokkaido.
  • D. Saca
    Saca is a Spanish-language surname most notably associated with former Salvadoran president Antonio Saca.
  • E. Tanto
    Tanto was a former town in Hyōgo Prefecture, Japan, that later became part of the expanded city of Toyooka through municipal merger.
  • 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: [Toma Erdődy, givenName, Toma]
Generated description
Toma is a masculine given name used in various European cultures, often as a form of Thomas.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Toma
Target entity description: Toma is a masculine given name used in various European cultures, often as a form of Thomas.
  • 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. Saca
    Saca is a Spanish-language surname most notably associated with former Salvadoran president Antonio Saca.
  • E. Tanto
    Tanto was a former town in Hyōgo Prefecture, Japan, that later became part of the expanded city of Toyooka through municipal merger.
  • 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_69d8b9f79d14819095540856928f0e25 completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e4ad95f4608190b1ebb45944218f07 completed April 19, 2026, 10:25 a.m.
NED1 Entity disambiguation (via context triple) batch_6a032914b7008190a7207d93f865ea8f completed May 12, 2026, 1:20 p.m.
NEDg Description generation batch_6a032b598bd881909f53df8f82799b6b completed May 12, 2026, 1:30 p.m.
NED2 Entity disambiguation (via description) batch_6a032c42d0a08190b2665adafaffdca7 completed May 12, 2026, 1:33 p.m.
Created at: April 10, 2026, 10:21 a.m.