Triple

T6099562
Position Surface form Disambiguated ID Type / Status
Subject central Iraq E135959 entity
Predicate includesCity P3207 FINISHED
Object Kut E68772 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: Kut | Statement: [central Iraq, includesCity, Kut]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kut
Context triple: [central Iraq, includesCity, Kut]
  • A. Kut chosen
    Kut is a city in eastern Iraq situated on the banks of the Tigris River, known historically as a strategic location and the site of significant World War I battles.
  • B. Kutiyana
    Kutiyana is a town in the Porbandar district of Gujarat, India, known historically as a local trading and administrative center.
  • C. Kuta
    Kuta is a popular beach resort town in southern Bali, Indonesia, known for its surfing waves, vibrant nightlife, and dense concentration of hotels, shops, and restaurants.
  • D. Kutelo
    Kutelo is one of the highest and most prominent peaks in Bulgaria’s Pirin mountain range, known for its sharp ridges and alpine terrain.
  • E. Kutchan
    Kutchan is a town in Hokkaido, Japan, known as a major access point to the Niseko ski resort area and for its heavy snowfall and potato farming.
  • 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_69c0087cd3c48190b459848c72d84eb1 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c05b3970808190ba90f5e4235db9f2 completed March 22, 2026, 9:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69c125475548819086b733a80056eba5 completed March 23, 2026, 11:34 a.m.
Created at: March 22, 2026, 4:13 p.m.