Triple

T14627521
Position Surface form Disambiguated ID Type / Status
Subject Anne of Bohemia and Luxembourg E343390 entity
Predicate givenName P17 FINISHED
Object Anne
Anne was a medieval European noblewoman from the royal houses of Bohemia and Luxembourg, notably Queen consort of England as the wife of King Richard II.
E999731 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: Anne | Statement: [Anne of Bohemia and Luxembourg, givenName, Anne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Anne
Context triple: [Anne of Bohemia and Luxembourg, givenName, Anne]
  • A. Anne
    Anne is traditionally revered in Christian tradition as the mother of the Virgin Mary and the grandmother of Jesus.
  • B. Anne
    Anne was the Queen of Great Britain and Ireland from 1702 to 1714, the last monarch of the House of Stuart.
  • C. Anne
    Anne is the protagonist of "The Darkest Hour," around whom the film’s central conflict and emotional journey revolve.
  • D. Anne
    Anne is one of the central child protagonists in Enid Blyton’s Famous Five adventure series, known for her kindness, domestic sense, and cautious nature.
  • E. Anne
    Anne is one of the child protagonists in Enid Blyton’s Famous Five series, known for her cautious nature and love of home comforts during the group’s adventures.
  • 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: Anne
Triple: [Anne of Bohemia and Luxembourg, givenName, Anne]
Generated description
Anne was a medieval European noblewoman from the royal houses of Bohemia and Luxembourg, notably Queen consort of England as the wife of King Richard II.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Anne
Target entity description: Anne was a medieval European noblewoman from the royal houses of Bohemia and Luxembourg, notably Queen consort of England as the wife of King Richard II.
  • A. Anne chosen
    Anne was a medieval European noblewoman, historically known as Anne of Bohemia, who lived from 1290 to 1313.
  • B. Anne
    Anne was the Duchess of Brittany who twice became Queen of France in the late 15th and early 16th centuries.
  • C. Anne
    Anne was a Polish queen consort of the early 17th century, known as the wife of King Sigismund III Vasa and a member of the Habsburg dynasty.
  • D. Anne
    Anne was the Queen of Great Britain and Ireland from 1702 to 1714, the last monarch of the House of Stuart.
  • E. Anne
    Anne of Gorizia-Tyrol was a 14th-century noblewoman from the Meinhardiner dynasty who became Duchess of Austria and Styria through her marriage to Duke Otto the Merry.
  • F. None of above.

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_69d822dffc3c8190aa173b90761bffda completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb4a7c8fc81909d10c1f563d7d1e7 completed April 14, 2026, 9:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69fda90c365481908a8a060cb1908775 completed May 8, 2026, 9:12 a.m.
NEDg Description generation batch_69fdb2c3d85481909021d924a2d660bb completed May 8, 2026, 9:54 a.m.
NED2 Entity disambiguation (via description) batch_69fdb3f34578819099e67be907eb1b7d completed May 8, 2026, 9:59 a.m.
Created at: April 10, 2026, 1:26 a.m.