Triple

T1998226
Position Surface form Disambiguated ID Type / Status
Subject Lake Elsinore E43404 entity
Predicate hasNearbyCity P350 FINISHED
Object Corona E76819 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: Corona | Statement: [Lake Elsinore, hasNearbyCity, Corona]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Corona
Context triple: [Lake Elsinore, hasNearbyCity, Corona]
  • A. Corona
    Corona is a globally popular Mexican beer brand produced by Grupo Modelo and widely associated with sports sponsorships and beach-themed marketing.
  • B. Corona, California chosen
    Corona, California is a rapidly growing suburban city in Riverside County known for its residential communities, proximity to major Southern California freeways, and role as a gateway between Orange County and the Inland Empire.
  • C. Kota
    Kota is a major industrial and educational city in southeastern Rajasthan, India, known for its coaching institutes and power plants along the Chambal River.
  • D. Kokota
    Kokota is an Oceanic language spoken in the Solomon Islands, particularly on Santa Isabel Island.
  • E. Soest
    Soest is a historic town in North Rhine-Westphalia, Germany, known for its well-preserved medieval architecture and former significance as a Hanseatic trading center.
  • 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_69a88715dbbc8190b2299e29e955d997 completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb867c49081909a9ca5fa21bf7aa3 completed March 7, 2026, 5:32 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae033e733c8190aa11e316e01dbd17 completed March 8, 2026, 11:16 p.m.
Created at: March 4, 2026, 7:37 p.m.