Triple

T7325110
Position Surface form Disambiguated ID Type / Status
Subject Lotte Orions E168850 entity
Predicate sponsor P67 FINISHED
Object Lotte E613191 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: Lotte | Statement: [Lotte Orions, sponsor, Lotte]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lotte
Context triple: [Lotte Orions, sponsor, Lotte]
  • A. Lotte Group chosen
    Lotte Group is a major South Korean-Japanese multinational conglomerate with diverse businesses spanning food, retail, tourism, chemicals, and entertainment.
  • B. Hansol
    Hansol is a locality in Ahmedabad, India, situated near Sardar Vallabhbhai Patel International Airport and known primarily as a residential and commercial area serving airport-related activities.
  • C. Shinsegae Group
    Shinsegae Group is a major South Korean retail conglomerate best known for its department stores, supermarkets, and diverse consumer-focused businesses.
  • D. Lotte Orions
    Lotte Orions was a Japanese professional baseball team in Nippon Professional Baseball, known as a predecessor to the Chiba Lotte Marines.
  • E. Sojin
    Sojin is a given name, often used in East Asian cultures, that can refer to various individuals in entertainment, arts, and other fields.
  • 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_69c68a54cacc81908e3b773441f19566 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f04993408190b73fb46d83a632d5 completed March 27, 2026, 9:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7fa7bfe248190a5def09d6941e114 completed March 28, 2026, 3:57 p.m.
Created at: March 27, 2026, 3:03 p.m.