Triple

T17796469
Position Surface form Disambiguated ID Type / Status
Subject Preah Ko E444304 entity
Predicate nearbySite P350 FINISHED
Object Lolei 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: Lolei | Statement: [Preah Ko, nearbySite, Lolei]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lolei
Context triple: [Preah Ko, nearbySite, Lolei]
  • A. Lolei chosen
    Lolei is an ancient temple in Cambodia’s Angkor region, known as one of the Roluos Group of early Khmer brick towers built during the late 9th century.
  • B. Laleia
    Laleia is a town in northern Timor-Leste known as the birthplace of independence leader and former president Xanana Gusmão.
  • C. Ta’aisha
    The Ta’aisha are a Sudanese Arab tribal group from the Darfur–Kordofan region, historically prominent through their leadership role in the Mahdist state under Abdallahi ibn Muhammad.
  • D. Kaiya
    Kaiya is a feminine given name used in various cultures, often associated with meanings related to the sea, forgiveness, or purity.
  • E. Reona
    Reona is the Japanese given name of Nobel Prize–winning physicist Leo Esaki, known for his pioneering work on quantum tunneling and semiconductor devices.
  • 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_69d8b9efe370819095cd219b143ae727 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e487fafc2c8190b28e791267c47e3c completed April 19, 2026, 7:44 a.m.
Created at: April 10, 2026, 10:13 a.m.