Triple

T10524885
Position Surface form Disambiguated ID Type / Status
Subject GW SEAS E248274 entity
Predicate shortName P43 FINISHED
Object GW SEAS E248274 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: GW SEAS | Statement: [GW SEAS, shortName, GW SEAS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: GW SEAS
Context triple: [GW SEAS, shortName, GW SEAS]
  • A. GW SEAS chosen
    GW SEAS is the engineering and applied science school of The George Washington University, offering programs in fields such as engineering, computer science, and related technologies.
  • B. SEAS
    SEAS is an abbreviation commonly used to refer to the Seattle Aquarium, a major public aquarium and marine conservation institution located on the waterfront in Seattle, Washington.
  • C. SEAS
    SEAS is the acronym for Yale University's School of Engineering & Applied Science, which houses its engineering and applied science programs.
  • D. SEAS
    SEAS is the University of Pennsylvania’s engineering and applied science school, offering undergraduate and graduate programs in fields such as computer science, bioengineering, and mechanical engineering.
  • E. SEAS
    SEAS is the abbreviation for the Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University's engineering and applied sciences school.
  • 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_69d381c5c7448190bec34bee7ec72bac completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d509f4020c8190b78c49da086df757 completed April 7, 2026, 1:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69d90e1c73208190aa3d3e30aa4482ac completed April 10, 2026, 2:50 p.m.
Created at: April 6, 2026, 12:29 p.m.