Triple

T9810662
Position Surface form Disambiguated ID Type / Status
Subject Giacomo Meyerbeer E238261 entity
Predicate notableWork P4 FINISHED
Object Dinorah
Dinorah is a 19th-century French opéra comique by Giacomo Meyerbeer, known for its virtuosic coloratura writing and pastoral, supernatural-themed story.
 E822621 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: Dinorah | Statement: [Giacomo Meyerbeer, notableWork, Dinorah]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Dinorah
Context triple: [Giacomo Meyerbeer, notableWork, Dinorah]
  • A. Leonora
    Leonora is a remote mining town in Western Australia’s Goldfields-Esperance region, historically significant for its goldfields and outback heritage.
  • B. Leonora
    Leonora is a feminine given name used in various cultures, often considered a variant of Eleanor or Leonore.
  • C. Berenice
    Berenice is a feminine given name of Greek origin, historically borne by Hellenistic queens and early Christian figures, and used in various European languages.
  • D. Delilah
    Delilah is a biblical figure best known for betraying Samson by discovering and revealing the secret of his strength.
  • E. Delilah
    Delilah is a drama television series that serves as a spin-off of the church-centered family saga Greenleaf, focusing on new characters and legal and personal conflicts.
  • 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: Dinorah
Triple: [Giacomo Meyerbeer, notableWork, Dinorah]
Generated description
Dinorah is a 19th-century French opéra comique by Giacomo Meyerbeer, known for its virtuosic coloratura writing and pastoral, supernatural-themed story.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Dinorah
Target entity description: Dinorah is a 19th-century French opéra comique by Giacomo Meyerbeer, known for its virtuosic coloratura writing and pastoral, supernatural-themed story.
  • A. Leonora
    Leonora is a remote mining town in Western Australia’s Goldfields-Esperance region, historically significant for its goldfields and outback heritage.
  • B. Leonora
    Leonora is a feminine given name used in various cultures, often considered a variant of Eleanor or Leonore.
  • C. Berenice
    Berenice is a feminine given name of Greek origin, historically borne by Hellenistic queens and early Christian figures, and used in various European languages.
  • D. Delilah
    Delilah is a biblical figure best known for betraying Samson by discovering and revealing the secret of his strength.
  • E. Delilah
    Delilah is a drama television series that serves as a spin-off of the church-centered family saga Greenleaf, focusing on new characters and legal and personal conflicts.
  • 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_69ca84defac48190abc1148804f184c1 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb2214a7c8190b516acf64e2b85db completed April 2, 2026, 12:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1cc5f768c8190987aaa7164f42444 completed April 5, 2026, 2:43 a.m.
NEDg Description generation batch_69d1ccd04b60819085a5bde42605ecf5 completed April 5, 2026, 2:45 a.m.
NED2 Entity disambiguation (via description) batch_69d1cd70aa5481908b67afef279c38af completed April 5, 2026, 2:48 a.m.
Created at: March 30, 2026, 8:30 p.m.