Triple

T4078016
Position Surface form Disambiguated ID Type / Status
Subject S-57 E87410 entity
Predicate successorStandard P101 FINISHED
Object S-100 E87411 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: S-100 | Statement: [S-57, successorStandard, S-100]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: S-100
Context triple: [S-57, successorStandard, S-100]
  • A. S-100 chosen
    S-100 is a modern, universal hydrographic data model and framework used as the basis for next-generation electronic navigational charts and related marine geospatial products.
  • B. C-10
    C-10 is a commuter rail line within the Cercanías Madrid network that connects central Madrid with its surrounding metropolitan areas.
  • C. Niva
    Niva was a prominent Russian literary and illustrated weekly magazine of the late 19th and early 20th centuries, known for publishing fiction, poetry, and cultural commentary.
  • D. SR-91
    SR-91 is a state highway designation commonly used in the United States for a numbered route within a state's road network.
  • E. S-101
    S-101 is the International Hydrographic Organization’s modern electronic navigational chart standard designed to support next-generation marine navigation systems.
  • 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_69aed9435cf48190ad1da737c962d19d completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefc4d348c8190a94724639830aca0 completed March 9, 2026, 4:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69b562bea9b48190bcd1396c0cb19697 completed March 14, 2026, 1:29 p.m.
Created at: March 9, 2026, 3:39 p.m.