Triple

T14694657
Position Surface form Disambiguated ID Type / Status
Subject Lili Elbe E345121 entity
Predicate surgeryLocation P8558 FINISHED
Object Dresden E37454 NE FINISHED

How this triple was built (3 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: Dresden | Statement: [Lili Elbe, surgeryLocation, Dresden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dresden
Context triple: [Lili Elbe, surgeryLocation, Dresden]
  • A. Dresden
    Dresden is a small community within the municipality of Chatham-Kent in southwestern Ontario, Canada, known historically for its role in the Underground Railroad and Black settlement.
  • B. Dresden chosen
    Dresden is a historic cultural and economic center in eastern Germany, renowned for its baroque architecture, art collections, and reconstruction after World War II.
  • C. Leipzig
    Leipzig is a major city in eastern Germany known for its rich cultural heritage, vibrant music and arts scene, and important role in trade and commerce.
  • D. Chemnitz
    Chemnitz is a city in eastern Germany known for its industrial heritage and post-reunification urban redevelopment.
  • E. Magdeburg
    Magdeburg is a historic city in central Germany, known for its medieval cathedral, role as a major trading and industrial center, and location on the Elbe River.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: surgeryLocation
Context triple: [Lili Elbe, surgeryLocation, Dresden]
  • A. involvedLocation
    Indicates that an event, action, or relationship takes place in, or is significantly associated with, a particular location.
  • B. treatmentLocation chosen
    Indicates the place or facility where a treatment or medical intervention is administered to an entity.
  • C. surgicalField
    Indicates the specific anatomical area or region of the body on which a surgical procedure is performed.
  • D. examinationLocation
    Indicates the place or setting where an examination or test is conducted.
  • E. operationLocation
    Indicates the place or site where an operation, activity, or process is carried out.
  • F. None of above.

Provenance (4 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_69d822e34b348190ada4d1cdb6c7c226 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb586e7108190be644db9cf9a4d99 completed April 14, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff0b3017808190a44087056ba6a472 completed May 9, 2026, 10:23 a.m.
PD Predicate disambiguation batch_69de657c57ec8190ae0b9bb79a514566 completed April 14, 2026, 4:04 p.m.
Created at: April 10, 2026, 1:28 a.m.