Triple

T23179022
Position Surface form Disambiguated ID Type / Status
Subject Montse Tomé E579099 entity
Predicate familyName P18 FINISHED
Object Tomé
Tomé is a Spanish surname borne by various notable individuals, including figures in sports, politics, and the arts.
E1573906 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: Tomé | Statement: [Montse Tomé, familyName, Tomé]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tomé
Context triple: [Montse Tomé, familyName, Tomé]
  • A. Tomé
    Tomé is a small unincorporated community in Valencia County, New Mexico, known historically as a Spanish colonial settlement along the Rio Grande.
  • B. Tomé
    Tomé is a coastal commune and city in Chile’s Biobío Region, known for its textile industry, fishing activities, and beaches.
  • C. Santo Tomás
    Santo Tomás is a town in the Cusco Region of Peru that serves as the administrative and commercial center of Chumbivilcas Province.
  • D. Santo Tomás
    Santo Tomás is a municipality in El Salvador known for its rural character and proximity to the capital, San Salvador.
  • E. Santo Tomás
    Santo Tomás is a small settlement within Cuba’s Ciénaga de Zapata region, known for its proximity to extensive wetlands and rich biodiversity.
  • 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: Tomé
Triple: [Montse Tomé, familyName, Tomé]
Generated description
Tomé is a Spanish surname borne by various notable individuals, including figures in sports, politics, and the arts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tomé
Target entity description: Tomé is a Spanish surname borne by various notable individuals, including figures in sports, politics, and the arts.
  • A. Tomé
    Tomé is a coastal commune and city in Chile’s Biobío Region, known for its textile industry, fishing activities, and beaches.
  • B. Tomé
    Tomé is a small unincorporated community in Valencia County, New Mexico, known historically as a Spanish colonial settlement along the Rio Grande.
  • C. Santo Tomás
    Santo Tomás is a municipality in El Salvador known for its rural character and proximity to the capital, San Salvador.
  • D. Santo Tomás
    Santo Tomás is a town in the Cusco Region of Peru that serves as the administrative and commercial center of Chumbivilcas Province.
  • E. Santo Tomás
    Santo Tomás is a small rural settlement located in the Collón Curá Department of Neuquén Province in Argentine Patagonia.
  • 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_69e245fd2a388190b814c0dfa15f7148 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f18f6dad948190a64f80f2c9e8e4cb completed April 29, 2026, 4:56 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0c30b0157c81909f0dad0a84b0af33 completed May 19, 2026, 9:43 a.m.
NEDg Description generation batch_6a0c349e5f988190a801356107a6e129 completed May 19, 2026, 9:59 a.m.
NED2 Entity disambiguation (via description) batch_6a0c3505873c81908ce41f3fa88c61b9 completed May 19, 2026, 10:01 a.m.
Created at: April 17, 2026, 4:04 p.m.