Triple

T9542576
Position Surface form Disambiguated ID Type / Status
Subject Mary Region E230193 entity
Predicate hasCity P316 FINISHED
Object Yolöten
Yolöten is a town in Turkmenistan’s Mary Region, known as a local administrative and agricultural center in the southeastern part of the country.
 E805785 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: Yolöten | Statement: [Mary Region, hasCity, Yolöten]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Yolöten
Context triple: [Mary Region, hasCity, Yolöten]
  • A. Lödöse
    Lödöse is a historic Swedish town that was one of the country’s earliest and most important medieval trading centers, located in the province of Västergötland.
  • B. Drongen
    Drongen is a district of the Belgian city of Ghent, known as a suburban area in East Flanders.
  • C. Heldrungen
    Heldrungen is a small town in the German state of Thuringia, notable for its historic water castle and location near the confluence of the Unstrut and Wipper rivers.
  • D. Lotha
    Lotha is a Naga ethnic group primarily inhabiting the Wokha district of Nagaland in Northeast India, known for its rich cultural traditions and festivals.
  • E. Lappidoth
    Lappidoth is a biblical figure mentioned in the Book of Judges as the husband of the prophetess and judge Deborah.
  • 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: Yolöten
Triple: [Mary Region, hasCity, Yolöten]
Generated description
Yolöten is a town in Turkmenistan’s Mary Region, known as a local administrative and agricultural center in the southeastern part of the country.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Yolöten
Target entity description: Yolöten is a town in Turkmenistan’s Mary Region, known as a local administrative and agricultural center in the southeastern part of the country.
  • A. Lödöse
    Lödöse is a historic Swedish town that was one of the country’s earliest and most important medieval trading centers, located in the province of Västergötland.
  • B. Drongen
    Drongen is a district of the Belgian city of Ghent, known as a suburban area in East Flanders.
  • C. Heldrungen
    Heldrungen is a small town in the German state of Thuringia, notable for its historic water castle and location near the confluence of the Unstrut and Wipper rivers.
  • D. Lotha
    Lotha is a Naga ethnic group primarily inhabiting the Wokha district of Nagaland in Northeast India, known for its rich cultural traditions and festivals.
  • E. Lappidoth
    Lappidoth is a biblical figure mentioned in the Book of Judges as the husband of the prophetess and judge Deborah.
  • 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_69ca847c70b8819088a0a0bad64a50d6 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd98e9be048190bf1f01884ff7c362 completed April 1, 2026, 10:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69d14c6538b08190a9f81304214a876d completed April 4, 2026, 5:37 p.m.
NEDg Description generation batch_69d14d44b7f08190b66fecb315b37535 completed April 4, 2026, 5:41 p.m.
NED2 Entity disambiguation (via description) batch_69d14e0823e881908ed723d20f14789b completed April 4, 2026, 5:44 p.m.
Created at: March 30, 2026, 8:01 p.m.