Triple

T13177166
Position Surface form Disambiguated ID Type / Status
Subject WPES E313126 entity
Predicate abbreviation P43 FINISHED
Object WPES E313126 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: WPES | Statement: [WPES, abbreviation, WPES]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: WPES
Context triple: [WPES, abbreviation, WPES]
  • A. WPES chosen
    WPES is the ACM Workshop on Privacy in the Electronic Society, a leading academic forum for research on privacy and security issues in digital environments.
  • B. WCP
    WCP is the abbreviation for the World Climate Programme, an international initiative focused on understanding and addressing global climate variability and change.
  • C. WCP
    WCP is the abbreviation for the World’s Children’s Prize, a global educational and rights initiative that empowers children to learn about and support child rights and child-rights advocates.
  • D. WP
    WP is the reporting mark and common abbreviation for the Western Pacific Railroad, a historic American railroad that operated primarily in California and the western United States.
  • E. WPN
    WPN is the vehicle registration code assigned to the town of Płońsk in Poland.
  • 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_69d806ac3ee081909b2fd27d060aa974 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98c322fdc8190b05f2287eba9dda6 completed April 10, 2026, 11:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6f5ea93bc81908087326b3d043727 completed May 3, 2026, 7:14 a.m.
Created at: April 9, 2026, 9:14 p.m.