Triple

T13328221
Position Surface form Disambiguated ID Type / Status
Subject Gecekondu tribünü E317496 entity
Predicate hasChantTheme P15355 FINISHED
Object love for Ankaragücü LITERAL 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: love for Ankaragücü | Statement: [Gecekondu tribünü, hasChantTheme, love for Ankaragücü]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasChantTheme
Context triple: [Gecekondu tribünü, hasChantTheme, love for Ankaragücü]
  • A. hasChant chosen
    Indicates that an entity is associated with or characterized by a particular chant.
  • B. hasChantStyleHook
    Indicates that something possesses or is associated with a specific chant-style hook as a characteristic or feature.
  • C. hasSayingTheme
    Indicates that a saying, proverb, or quoted expression is about or centers on a particular theme or subject.
  • D. hasLyricsTheme
    Indicates that the lyrics of a work primarily concern or revolve around a specified theme or subject.
  • E. hasLyricalTheme
    Indicates that one entity (typically a creative work) features or is characterized by a particular lyrical subject, topic, or theme.
  • F. None of above.

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_69d806b4d62c81908d4ced1665414be5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d99cfdc9388190af1fdd3cd4717bd8 completed April 11, 2026, 12:59 a.m.
PD Predicate disambiguation batch_69d98f6babd88190a5d529df9584b9a4 completed April 11, 2026, 12:01 a.m.
Created at: April 9, 2026, 9:30 p.m.