Triple

T22386113
Position Surface form Disambiguated ID Type / Status
Subject Faculty of Nursing, University of North Sumatra E553399 entity
Predicate city P40 FINISHED
Object Medan 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: Medan | Statement: [Faculty of Nursing, University of North Sumatra, city, Medan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Medan
Context triple: [Faculty of Nursing, University of North Sumatra, city, Medan]
  • A. Medan
    Medan is a minor biblical figure mentioned in the Book of Genesis as one of the sons of Abraham by his wife Keturah.
  • B. Medan chosen
    Medan is a major economic and cultural hub in northern Sumatra, known as one of Indonesia’s largest cities and a gateway to the region.
  • C. Padang Sidempuan
    Padang Sidempuan is a city in western Indonesia known as a regional center in the southern part of North Sumatra province.
  • D. Tanjungbalai
    Tanjungbalai is a coastal city and port in northeastern Sumatra, Indonesia, known for its fishing industry and location along the Asahan River.
  • E. Binjai
    Binjai is a city in Indonesia located near Medan on the island of Sumatra, known as a regional trade and transit hub.
  • 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_69e11e4cf87c8190a1ff474daec326b7 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f1582f5f348190881df0d5af110aef completed April 29, 2026, 1 a.m.
Created at: April 16, 2026, 8:45 p.m.