Triple

T28496859
Position Surface form Disambiguated ID Type / Status
Subject Akdamar Island E721127 entity
Predicate hasAlternativeTransliteration P5923 FINISHED
Object Akhtamar Island
Akhtamar Island is a small island in Lake Van in eastern Turkey, best known for its medieval Armenian Holy Cross Church and rich cultural and historical significance.
E1824176 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: Akhtamar Island | Statement: [Akdamar Island, hasAlternativeTransliteration, Akhtamar Island]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Akhtamar Island
Triple: [Akdamar Island, hasAlternativeTransliteration, Akhtamar Island]
Generated description
Akhtamar Island is a small island in Lake Van in eastern Turkey, best known for its medieval Armenian Holy Cross Church and rich cultural and historical significance.

Provenance (5 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_69f01a5afdac8190ac6e72d5c100bd58 completed April 28, 2026, 2:24 a.m.
NER Named-entity recognition batch_69f64f3fc8dc8190a5f4179694686917 completed May 2, 2026, 7:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1cb6d6db388190ac5adf44a18257b1 completed May 31, 2026, 10:31 p.m.
NEDg Description generation batch_6a1cb92cead88190abd0ad73c3eb8ce6 completed May 31, 2026, 10:41 p.m.
NED2 Entity disambiguation (via description) batch_6a1cb9c3e8e88190bf5c5955adf18073 completed May 31, 2026, 10:44 p.m.
Created at: April 28, 2026, 3:04 a.m.