Triple

T10607043
Position Surface form Disambiguated ID Type / Status
Subject Secretaría de Educación Pública E275901 entity
Predicate shortName P43 FINISHED
Object SEP E275901 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: SEP | Statement: [Secretaría de Educación Pública, shortName, SEP]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SEP
Context triple: [Secretaría de Educación Pública, shortName, SEP]
  • A. SEP chosen
    SEP is the Mexican federal government department responsible for overseeing and regulating the national education system.
  • B. SEP
    SEP is the commonly used abbreviation for Sociedade Esportiva Palmeiras, one of Brazil’s most successful and popular football clubs.
  • C. SEP
    SEP is a peer-reviewed, open-access online reference work that provides in-depth scholarly articles on a wide range of topics in philosophy.
  • D. SER
    SER is the commonly used abbreviation for South Eastern Railway, a major railway zone in India.
  • E. SES
    SES is the abbreviation for the Senior Executive Service, the corps of top-level civilian managers and executives in the U.S. federal government.
  • 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_69d6aaf948d88190806cc3a8c47a3fb2 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d6df4b7aa48190bf7873b293571030 completed April 8, 2026, 11:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69d95eb726bc8190a8db7357bd126016 completed April 10, 2026, 8:33 p.m.
Created at: April 8, 2026, 7:32 p.m.