Triple

T17096387
Position Surface form Disambiguated ID Type / Status
Subject Javanese literature E414861 entity
Predicate hasWritingSystem P454 FINISHED
Object Pegon script E39178 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: Pegon script | Statement: [Javanese literature, hasWritingSystem, Pegon script]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pegon script
Context triple: [Javanese literature, hasWritingSystem, Pegon script]
  • A. Pegon script chosen
    Pegon script is an adapted form of the Arabic script traditionally used by Javanese and Sundanese Muslims to write their local languages, especially for religious and literary texts.
  • B. PYG
    PYG is the National Rail station code for Paisley Gilmour Street, a major railway station in Paisley, Scotland.
  • C. Mon script
    Mon script is an abugida writing system historically used by the Mon people of Southeast Asia and influential in the development of several other regional scripts, including Burmese.
  • D. PEG
    PEG is a German vehicle registration code assigned to the Bayreuth district region.
  • E. PEG
    PEG is the stock ticker symbol for Public Service Enterprise Group, a major U.S. energy company primarily involved in regulated electric and gas utility operations and power generation.
  • 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_69d886cfc8e88190b05ba466edd35591 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3dbfdc9c88190b4e75bbdf4105c1e completed April 18, 2026, 7:31 p.m.
NED1 Entity disambiguation (via context triple) batch_6a012eedfd7c8190b267dedd403f5f2b completed May 11, 2026, 1:20 a.m.
Created at: April 10, 2026, 5:35 a.m.