Triple

T1137481
Position Surface form Disambiguated ID Type / Status
Subject Ladin language E23172 entity
Predicate hasDialect P4251 FINISHED
Object Anpezan
Anpezan is a regional dialect of the Ladin language spoken in parts of the Dolomite area of northern Italy.
 E130780 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: Anpezan | Statement: [Ladin language, hasDialect, Anpezan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Anpezan
Context triple: [Ladin language, hasDialect, Anpezan]
  • A. Darzalex
    Darzalex is a monoclonal antibody drug (daratumumab) used primarily in the treatment of multiple myeloma.
  • B. Vumerity
    Vumerity is an oral prescription medication used to treat relapsing forms of multiple sclerosis in adults.
  • C. Versonnex
    Versonnex is a small commune in the Ain department of eastern France, located near the Swiss border in the Pays de Gex region.
  • D. Plegridy
    Plegridy is a pegylated interferon beta-1a medication used to treat relapsing forms of multiple sclerosis.
  • E. Denesuline
    Denesuline are a First Nations people of the larger Dene cultural and linguistic group, traditionally inhabiting subarctic regions of northern Canada.
  • 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: Anpezan
Triple: [Ladin language, hasDialect, Anpezan]
Generated description
Anpezan is a regional dialect of the Ladin language spoken in parts of the Dolomite area of northern Italy.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Anpezan
Target entity description: Anpezan is a regional dialect of the Ladin language spoken in parts of the Dolomite area of northern Italy.
  • A. Darzalex
    Darzalex is a monoclonal antibody drug (daratumumab) used primarily in the treatment of multiple myeloma.
  • B. Vumerity
    Vumerity is an oral prescription medication used to treat relapsing forms of multiple sclerosis in adults.
  • C. Versonnex
    Versonnex is a small commune in the Ain department of eastern France, located near the Swiss border in the Pays de Gex region.
  • D. Plegridy
    Plegridy is a pegylated interferon beta-1a medication used to treat relapsing forms of multiple sclerosis.
  • E. Denesuline
    Denesuline are a First Nations people of the larger Dene cultural and linguistic group, traditionally inhabiting subarctic regions of northern Canada.
  • 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_69a493ec75988190b63a11bafaec29b4 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4bc2450c481909b9264e170070326 completed March 1, 2026, 10:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac59ae5f20819093f8acc3ba7a6638 completed March 7, 2026, 5 p.m.
NEDg Description generation batch_69ac5b5e2c688190a7d4998a3ed0f443 completed March 7, 2026, 5:07 p.m.
NED2 Entity disambiguation (via description) batch_69ac5bb6e78c8190a34ecbc246f72ff6 completed March 7, 2026, 5:09 p.m.
Created at: March 1, 2026, 7:44 p.m.