Triple

T12901083
Position Surface form Disambiguated ID Type / Status
Subject Schuylkill Action Network E308612 entity
Predicate abbreviation P43 FINISHED
Object SAN E308612 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: SAN | Statement: [Schuylkill Action Network, abbreviation, SAN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SAN
Context triple: [Schuylkill Action Network, abbreviation, SAN]
  • A. SAN
    SAN is the three-letter IATA airport code for San Diego International Airport, the primary commercial airport serving the San Diego, California area.
  • B. SAN chosen
    SAN is the acronym for the Schuylkill Action Network, a collaborative partnership focused on protecting and restoring the Schuylkill River watershed.
  • C. SAN
    SAN is the stock ticker symbol for Banco Santander S.A., a major Spanish multinational banking and financial services company.
  • D. SAN
    SAN is the vehicle registration code used on license plates for vehicles registered in the Hof district of Bavaria, Germany.
  • E. SAM
    SAM is the official FIFA trigramme used to represent the Samoa national under-20 football team in international competitions and records.
  • 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_69d7bdf7c1f0819098102569a8d8cbf5 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d97180ee708190b60a3e58c42f764f completed April 10, 2026, 9:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6a56189b081909ed838addcb6d265 completed May 3, 2026, 1:31 a.m.
Created at: April 9, 2026, 5:40 p.m.