Triple

T9190777
Position Surface form Disambiguated ID Type / Status
Subject Dobre Miasto E220582 entity
Predicate carPlates P1173 FINISHED
Object NOL E783892 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: NOL | Statement: [Dobre Miasto, carPlates, NOL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: NOL
Context triple: [Dobre Miasto, carPlates, NOL]
  • A. NOL
    NOL is the Amtrak station code for New Orleans’ main intercity rail hub, the New Orleans Union Passenger Terminal.
  • B. NOL chosen
    NOL is a Polish vehicle registration code assigned to cars registered in the Olsztyn County area, which includes the town of Jeziorany.
  • C. Nol
    Nol is the given name of Lon Nol, the Cambodian military leader and politician who served as Prime Minister and later led the Khmer Republic in the early 1970s.
  • D. NOB
    NOB is the abbreviation for the Schweizerische Nordostbahn, a former Swiss railway company that operated in northeastern Switzerland in the 19th and early 20th centuries.
  • E. NOB
    NOB is the abbreviation for Dutch National Opera & Ballet, the leading institution for opera and ballet performances in the Netherlands.
  • 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_69ca83e7ba70819088b74866d9da2c30 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccd5bf25c081909e651b67ef8ecc33 completed April 1, 2026, 8:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69d077797be081908300a5baa0041ce5 completed April 4, 2026, 2:29 a.m.
Created at: March 30, 2026, 7:24 p.m.