Triple

T22419233
Position Surface form Disambiguated ID Type / Status
Subject ABA Section of Environment, Energy, and Resources E554201 entity
Predicate hasAbbreviation P43 FINISHED
Object SEER NE NERFINISHED

How this triple was built (3 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: SEER | Statement: [ABA Section of Environment, Energy, and Resources, hasAbbreviation, SEER]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SEER
Context triple: [ABA Section of Environment, Energy, and Resources, hasAbbreviation, SEER]
  • A. SEUR
    SEUR is a Spanish express parcel and logistics company operating under the international DPDgroup network.
  • B. SEV
    SEV is the National Rail station code for Sevenoaks railway station in Kent, England.
  • C. SEEL
    SEEL is the abbreviation for the Space Environmental Effects Laboratory, a facility focused on studying how the space environment impacts materials and systems.
  • D. SEREB
    SEREB was a French aerospace company involved in the development of ballistic missiles and space launch vehicles before being merged into Aérospatiale.
  • E. SÉG
    SÉG is the station code for Ségur, a Paris Métro station on Line 10 in the 15th arrondissement of Paris, France.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: SEER
Target entity description: SEER is the commonly used abbreviation for the American Bar Association’s Section of Environment, Energy, and Resources, a leading forum for lawyers and professionals focused on environmental, energy, and natural resources law.
  • A. SEUR
    SEUR is a Spanish express parcel and logistics company operating under the international DPDgroup network.
  • B. SEV
    SEV is the National Rail station code for Sevenoaks railway station in Kent, England.
  • C. SEEL
    SEEL is the abbreviation for the Space Environmental Effects Laboratory, a facility focused on studying how the space environment impacts materials and systems.
  • D. SEREB
    SEREB was a French aerospace company involved in the development of ballistic missiles and space launch vehicles before being merged into Aérospatiale.
  • E. SÉG
    SÉG is the station code for Ségur, a Paris Métro station on Line 10 in the 15th arrondissement of Paris, France.
  • F. None of above. chosen

Provenance (2 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_69e11e4e6ce8819085a1e06d886bf21c completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15948dcdc81909d0a792c4498fa70 completed April 29, 2026, 1:05 a.m.
Created at: April 16, 2026, 8:46 p.m.