Triple

T1742337
Position Surface form Disambiguated ID Type / Status
Subject California Endangered Species Act E38260 entity
Predicate abbreviation P43 FINISHED
Object CESA E38260 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: CESA | Statement: [California Endangered Species Act, abbreviation, CESA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CESA
Context triple: [California Endangered Species Act, abbreviation, CESA]
  • A. CESA chosen
    CESA is a California state law that protects plant and animal species at risk of extinction by regulating activities that may harm them or their habitats.
  • B. CESAER
    CESAER is a European association of leading universities of science and technology that collaborates to advance engineering education, research, and innovation.
  • C. CESE
    CESE is France’s Economic, Social and Environmental Council, a constitutional advisory body that represents civil society and provides expert opinions on public policy.
  • D. ECASA
    ECASA is a Cuban state-owned company responsible for managing and operating the country’s civil airports and air terminals.
  • E. CSD
    CSD is the renowned Computer Science Department at Carnegie Mellon University, recognized globally for its pioneering research and education in computer science.
  • 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_69a8862b01a48190ab47209063af82d9 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa63c6d21c8190809bedaa798e2b14 completed March 6, 2026, 5:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad8b0ab7008190a2fafe1c8ac55ac4 completed March 8, 2026, 2:43 p.m.
Created at: March 4, 2026, 7:30 p.m.