Triple

T11059555
Position Surface form Disambiguated ID Type / Status
Subject Tecnotex E261469 entity
Predicate parentOrganization P254 FINISHED
Object GAESA E46010 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: GAESA | Statement: [Tecnotex, parentOrganization, GAESA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: GAESA
Context triple: [Tecnotex, parentOrganization, GAESA]
  • A. GAESA chosen
    GAESA is a powerful Cuban military-owned business conglomerate that dominates key sectors of the country's economy, including tourism, retail, and real estate.
  • B. GES
    GES is the stock ticker symbol for Guess?, Inc., an American clothing and accessories retailer known for its denim and fashion apparel.
  • C. GSE
    GSE is the abbreviation commonly used for the Stanford Graduate School of Education, a leading institution for research and training in education.
  • D. GSE
    GSE is the IATA airport code for Gothenburg City Airport, a regional airport serving the Gothenburg area in Sweden.
  • E. GSE
    GSE is the Graduate School of Education at Portland State University, offering programs that prepare educators, counselors, and leaders in the field of education.
  • 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_69d6aa98650481908609c7c56bfa7902 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d798a4f3f88190a29710f64cef9d25 completed April 9, 2026, 12:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69e509b8c348819090f118fc69e3441f completed April 19, 2026, 4:58 p.m.
Created at: April 8, 2026, 9:26 p.m.