Triple

T20581206
Position Surface form Disambiguated ID Type / Status
Subject Skansen Kronan E505657 entity
Predicate nearbyAttraction P3449 FINISHED
Object Haga district NE NERFINISHED

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: Haga district | Statement: [Skansen Kronan, nearbyAttraction, Haga district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haga district
Context triple: [Skansen Kronan, nearbyAttraction, Haga district]
  • A. Haga district chosen
    Haga district is one of Gothenburg’s oldest and most picturesque neighborhoods, known for its well-preserved wooden houses, cobblestone streets, and cozy cafés.
  • B. Chupuro District
    Chupuro District is an administrative district located within Huancayo Province in the Junín Region of central Peru.
  • C. Nangang District
    Nangang District is a central urban district of Harbin, China, known as a major administrative, commercial, and educational hub of the city.
  • D. Nangang District
    Nangang District is an eastern district of Taipei, Taiwan, known for its technology parks, transportation hubs, and role as a growing center for business and innovation.
  • E. Sangin District
    Sangin District is a rural administrative district in northern Helmand Province, Afghanistan, known for its strategic location and intense military activity during the Afghan conflict.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4b9669c8190b8e81fc72817d42c completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6a90e98a88190b5cb077973f97e68 completed April 20, 2026, 10:30 p.m.
Created at: April 16, 2026, 11:40 a.m.