Triple

T15722071
Position Surface form Disambiguated ID Type / Status
Subject Suhl E381119 entity
Predicate nearbyMountain P10602 FINISHED
Object Dolmar
Dolmar is a prominent mountain in central Germany’s Thuringian region, known for its scenic landscapes and hiking opportunities near the town of Suhl.
E1174451 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: Dolmar | Statement: [Suhl, nearbyMountain, Dolmar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dolmar
Context triple: [Suhl, nearbyMountain, Dolmar]
  • A. Dorla
    Dorla are an indigenous Adivasi community of the Bastar region in central India, known for their distinct cultural traditions, language, and close relationship with forest-based livelihoods.
  • B. Dhordo
    Dhordo is a village in Gujarat, India, renowned as a gateway to the White Rann of Kutch and a popular desert tourism destination.
  • C. Dovadola
    Dovadola is a small Italian town and municipality in the Emilia-Romagna region, known for its historic center and scenic location in the Apennine foothills.
  • D. Dolgan
    Dolgan is a Turkic language spoken primarily by the Dolgan people in northern Siberia, especially in Russia’s Taymyr Peninsula.
  • E. Dargwa
    Dargwa is a Northeast Caucasian language spoken primarily by the Dargin people in the Republic of Dagestan, Russia.
  • 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: Dolmar
Triple: [Suhl, nearbyMountain, Dolmar]
Generated description
Dolmar is a prominent mountain in central Germany’s Thuringian region, known for its scenic landscapes and hiking opportunities near the town of Suhl.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Dolmar
Target entity description: Dolmar is a prominent mountain in central Germany’s Thuringian region, known for its scenic landscapes and hiking opportunities near the town of Suhl.
  • A. Dorla
    Dorla are an indigenous Adivasi community of the Bastar region in central India, known for their distinct cultural traditions, language, and close relationship with forest-based livelihoods.
  • B. Dhordo
    Dhordo is a village in Gujarat, India, renowned as a gateway to the White Rann of Kutch and a popular desert tourism destination.
  • C. Dovadola
    Dovadola is a small Italian town and municipality in the Emilia-Romagna region, known for its historic center and scenic location in the Apennine foothills.
  • D. Dolgan
    Dolgan is a Turkic language spoken primarily by the Dolgan people in northern Siberia, especially in Russia’s Taymyr Peninsula.
  • E. Dargwa
    Dargwa is a Northeast Caucasian language spoken primarily by the Dargin people in the Republic of Dagestan, Russia.
  • 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_69d86d9bf930819082b30cf6d169297c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e04fb0b51081908e652ec4992296fa completed April 16, 2026, 2:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff82f464008190ae0e79f50b9b3eb3 completed May 9, 2026, 6:54 p.m.
NEDg Description generation batch_69ff83b7a534819090e24491579376c3 completed May 9, 2026, 6:57 p.m.
NED2 Entity disambiguation (via description) batch_69ff844fa00c8190a47eb46394db097b completed May 9, 2026, 7 p.m.
Created at: April 10, 2026, 4:45 a.m.