Triple

T144224
Position Surface form Disambiguated ID Type / Status
Subject Robert E2918 entity
Predicate hasCognate P2525 FINISHED
Object Rupert
Rupert is a masculine given name of Germanic origin, closely related to the name Robert and historically borne by various European nobles and notable figures.
 E2918 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: Rupert | Statement: [Robert, hasCognate, Rupert]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Rupert
Context triple: [Robert, hasCognate, Rupert]
  • A. Herbert
    Herbert is a masculine given name of Germanic origin that has been borne by various notable figures, including U.S. President Herbert Hoover.
  • B. Robert
    Robert is a common masculine given name of Germanic origin, widely used in English-speaking countries.
  • C. Cecil
    Cecil is a masculine given name most famously associated with pioneering American film director and producer Cecil B. DeMille.
  • D. Nicholas
    Nicholas is a masculine given name of Greek origin, commonly used in many cultures and historically borne by numerous saints, rulers, and notable figures.
  • E. Ralph Stackpole
    Ralph Stackpole was an American sculptor and painter associated with the San Francisco art scene, known for his public works and contributions to New Deal–era projects.
  • 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: Rupert
Triple: [Robert, hasCognate, Rupert]
Generated description
Rupert is a masculine given name of Germanic origin, closely related to the name Robert and historically borne by various European nobles and notable figures.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Rupert
Target entity description: Rupert is a masculine given name of Germanic origin, closely related to the name Robert and historically borne by various European nobles and notable figures.
  • A. Herbert
    Herbert is a masculine given name of Germanic origin that has been borne by various notable figures, including U.S. President Herbert Hoover.
  • B. Robert chosen
    Robert is a common masculine given name of Germanic origin, widely used in English-speaking countries.
  • C. Cecil
    Cecil is a masculine given name most famously associated with pioneering American film director and producer Cecil B. DeMille.
  • D. Nicholas
    Nicholas is a masculine given name of Greek origin, commonly used in many cultures and historically borne by numerous saints, rulers, and notable figures.
  • E. Ralph Stackpole
    Ralph Stackpole was an American sculptor and painter associated with the San Francisco art scene, known for his public works and contributions to New Deal–era projects.
  • 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_69a2521e35c08190b28e5c9f1e3c9b59 completed Feb. 28, 2026, 2:25 a.m.
NER Named-entity recognition batch_69a257e935bc8190a03e54a10e9ba6f7 completed Feb. 28, 2026, 2:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69a389a873d48190ac41ff919027688a completed March 1, 2026, 12:34 a.m.
NEDg Description generation batch_69a38a1053fc819089599155120c3b83 completed March 1, 2026, 12:36 a.m.
NED2 Entity disambiguation (via description) batch_69a38a5b53bc8190bf87f9260850fe9b completed March 1, 2026, 12:37 a.m.
Created at: Feb. 28, 2026, 2:31 a.m.