Triple

T856943
Position Surface form Disambiguated ID Type / Status
Subject Amur Oblast E18512 entity
Predicate hasCity P316 FINISHED
Object Tynda
Tynda is a town in Russia’s Far East known as a major junction on the Baikal–Amur Mainline railway.
 E101698 NE FINISHED

How this triple was built (4 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: Tynda | Statement: [Amur Oblast, hasCity, Tynda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tynda
Context triple: [Amur Oblast, hasCity, Tynda]
  • A. Bladon
    Bladon is a village in Oxfordshire, England, best known as the burial place of Sir Winston Churchill.
  • B. Rhayader
    Rhayader is a small market town in Powys, mid Wales, known as a gateway to the Elan Valley reservoirs and surrounding Cambrian Mountains.
  • C. Tverya
    Tverya is the Hebrew name for Tiberias, an ancient city in northern Israel on the western shore of the Sea of Galilee known for its religious significance and hot springs.
  • D. Evessa
    Evessa is a professional basketball team based in Osaka, Japan, competing in the B.League.
  • E. Tvishi
    Tvishi is a semi-sweet white Georgian wine, typically made from Tsolikouri grapes and renowned for its delicate fruitiness and balanced acidity.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Tynda
Triple: [Amur Oblast, hasCity, Tynda]
Generated description
Tynda is a town in Russia’s Far East known as a major junction on the Baikal–Amur Mainline railway.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tynda
Target entity description: Tynda is a town in Russia’s Far East known as a major junction on the Baikal–Amur Mainline railway.
  • A. Bladon
    Bladon is a village in Oxfordshire, England, best known as the burial place of Sir Winston Churchill.
  • B. Rhayader
    Rhayader is a small market town in Powys, mid Wales, known as a gateway to the Elan Valley reservoirs and surrounding Cambrian Mountains.
  • C. Tverya
    Tverya is the Hebrew name for Tiberias, an ancient city in northern Israel on the western shore of the Sea of Galilee known for its religious significance and hot springs.
  • D. Evessa
    Evessa is a professional basketball team based in Osaka, Japan, competing in the B.League.
  • E. Tvishi
    Tvishi is a semi-sweet white Georgian wine, typically made from Tsolikouri grapes and renowned for its delicate fruitiness and balanced acidity.
  • F. None of above. chosen

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_69a4938bdd3c8190a954a3c11844d9cf completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4ac4d47508190b48d944aa2d881bf completed March 1, 2026, 9:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7a3c1ee4481909d5713122e5ad856 completed March 4, 2026, 3:15 a.m.
NEDg Description generation batch_69a7a5288338819089638d5c848735dd completed March 4, 2026, 3:21 a.m.
NED2 Entity disambiguation (via description) batch_69a7a63205308190b55b76116c0d5e7c completed March 4, 2026, 3:25 a.m.
Created at: March 1, 2026, 7:39 p.m.