Triple

T11885238
Position Surface form Disambiguated ID Type / Status
Subject Ngeremlengui State E282762 entity
Predicate hasSettlement P1068 FINISHED
Object Imeong E952031 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: Imeong | Statement: [Ngeremlengui State, hasSettlement, Imeong]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Imeong
Context triple: [Ngeremlengui State, hasSettlement, Imeong]
  • A. Imeong chosen
    Imeong is a village in Palau that serves as the administrative center of Ngeremlengui State on Babeldaob Island.
  • B. Myeong-bok
    Myeong-bok is the given name of Gojong, the 26th king of the Joseon dynasty and first emperor of the Korean Empire.
  • C. Yeoncheon
    Yeoncheon is a county in Gyeonggi Province, South Korea, known for its location near the Demilitarized Zone (DMZ) and its significant historical and military sites.
  • D. Koung-Khi
    Koung-Khi is an administrative department located in the West Region of Cameroon.
  • E. Miryang
    Miryang is a city in South Gyeongsang Province, South Korea, known for its scenic river valley setting, historical sites, and role as a regional transport and educational 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_69d6ab2a90b08190a4e818821cc93e6d completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8d3a02ad4819090faef0e0be732ee completed April 10, 2026, 10:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69f43fd661f481909b1f7609540e42d7 completed May 1, 2026, 5:53 a.m.
Created at: April 8, 2026, 9:44 p.m.