Triple

T12528830
Position Surface form Disambiguated ID Type / Status
Subject Carlota Thorkildsen E299506 entity
Predicate givenName P17 FINISHED
Object Carlota E293081 NE FINISHED

How this triple was built (2 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: Carlota | Statement: [Carlota Thorkildsen, givenName, Carlota]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Carlota
Context triple: [Carlota Thorkildsen, givenName, Carlota]
  • A. Carlota chosen
    Carlota is the feminine given name corresponding to Carlos, commonly used in Spanish- and Portuguese-speaking cultures.
  • B. La Carlota
    La Carlota is a component city in the province of Negros Occidental in the Philippines, known for its agricultural economy and historic sugar industry.
  • C. Enriqueta
    Enriqueta is a feminine given name of Spanish origin, often associated with historical and cultural figures in Spanish-speaking countries.
  • D. Borbona
    Borbona is a small Italian town and comune in the Lazio region, known for its rural setting in the Apennine mountains and traditional local culture.
  • E. Cayetana
    Cayetana is the given name of Cayetana Fitz-James Stuart, the 18th Duchess of Alba, a prominent Spanish aristocrat known for holding a record number of noble titles.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d6ada5cdd48190860d9ce30aff69be completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d9545e90948190980bd4d64964a0f2 completed April 10, 2026, 7:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69f67c6a590881908b0fe779f3698ea2 completed May 2, 2026, 10:36 p.m.
Created at: April 8, 2026, 9:57 p.m.