Triple

T5704970
Position Surface form Disambiguated ID Type / Status
Subject Krk Island E125760 entity
Predicate hasPort P35 FINISHED
Object Punat E460108 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: Punat | Statement: [Krk Island, hasPort, Punat]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Punat
Context triple: [Krk Island, hasPort, Punat]
  • A. Punat chosen
    Punat is a coastal town and popular tourist resort on the island of Krk in Croatia, known for its marina and proximity to the islet of Košljun.
  • B. Punnun
    Punnun is a legendary prince and tragic lover from the Sindhi and Balochi folktale "Sassi Punnun," renowned for his doomed romance with Sassi.
  • C. Punasa
    Punasa is a town in Madhya Pradesh, India, known for its proximity to the major Indira Sagar Dam on the Narmada River.
  • D. Paranesti
    Paranesti is a small town and municipality in northeastern Greece, known for its mountainous landscapes, forests, and proximity to the Nestos River.
  • E. Papine
    Papine is a community in the Parish of St. Andrew, Jamaica, known for its proximity to the University of the West Indies and its role as a busy commercial and transportation hub.
  • 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_69c0082c96988190b3a6a201edce472a completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c024585d14819098ec34fd5a858836 completed March 22, 2026, 5:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c07de7df8c8190824d24f729eaa04d completed March 22, 2026, 11:40 p.m.
Created at: March 22, 2026, 3:45 p.m.