Triple

T8806644
Position Surface form Disambiguated ID Type / Status
Subject Free Pascal E209548 entity
Predicate supportsOperatingSystem P5090 FINISHED
Object Haiku E209551 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: Haiku | Statement: [Free Pascal, supportsOperatingSystem, Haiku]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haiku
Context triple: [Free Pascal, supportsOperatingSystem, Haiku]
  • A. Haiku chosen
    Haiku is an open-source, lightweight desktop operating system inspired by BeOS, designed for speed, simplicity, and consistency.
  • B. tanka
    The tanka was a medieval silver coin that served as a standard monetary unit across much of the Indian subcontinent under various Islamic and later dynasties.
  • C. Temwaiku
    Temwaiku is a village and district within South Tarawa in Kiribati, known as one of the populated islets forming the country's capital area.
  • D. Haikasoru
    Haikasoru is a publishing imprint of Viz Media that specializes in translating and releasing Japanese science fiction and fantasy novels in English.
  • E. Kawi
    Kawi is an ancient Brahmic script historically used in maritime Southeast Asia, particularly for Old Javanese and related languages.
  • 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_69ca836320e48190b5cf585b90a322c4 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5fd1f1a08190a2e584f6b0495f5c completed March 31, 2026, 11:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf6f96bb448190b9316ad55d61662a completed April 3, 2026, 7:43 a.m.
Created at: March 30, 2026, 6:45 p.m.