Triple

T3604409
Position Surface form Disambiguated ID Type / Status
Subject Wolfram E76334 entity
Predicate hasNameElement P3097 FINISHED
Object hraban
Hraban is a Germanic given name element historically associated with figures such as the medieval scholar Rabanus Maurus and related to themes of counsel and wisdom.
 E371419 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: hraban | Statement: [Wolfram, hasNameElement, hraban]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: hraban
Context triple: [Wolfram, hasNameElement, hraban]
  • A. harae
    Harae is a central Shinto purification ritual intended to cleanse spiritual impurity and restore harmony between people, nature, and the kami.
  • B. Hor
    Hor is an abbreviated form of the name Horace, often used as a short or familiar version of it.
  • C. Ham
    Ham is a suburban riverside district in southwest London, England, known for its historic houses, green spaces, and proximity to the River Thames.
  • D. Ham
    Ham is a small town in the Somme department of northern France, known historically for its medieval fortress and strategic location.
  • E. HOR
    HOR is the IATA airport code for Horta Airport, which serves the island of Faial in Portugal’s Azores archipelago.
  • 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: hraban
Triple: [Wolfram, hasNameElement, hraban]
Generated description
Hraban is a Germanic given name element historically associated with figures such as the medieval scholar Rabanus Maurus and related to themes of counsel and wisdom.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: hraban
Target entity description: Hraban is a Germanic given name element historically associated with figures such as the medieval scholar Rabanus Maurus and related to themes of counsel and wisdom.
  • A. harae
    Harae is a central Shinto purification ritual intended to cleanse spiritual impurity and restore harmony between people, nature, and the kami.
  • B. Hor
    Hor is an abbreviated form of the name Horace, often used as a short or familiar version of it.
  • C. Ham
    Ham is a suburban riverside district in southwest London, England, known for its historic houses, green spaces, and proximity to the River Thames.
  • D. Ham
    Ham is a small town in the Somme department of northern France, known historically for its medieval fortress and strategic location.
  • E. HOR
    HOR is the IATA airport code for Horta Airport, which serves the island of Faial in Portugal’s Azores archipelago.
  • 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_69ad85d93dcc819094fba90cf70f4996 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc1e07bc481908d9fce18d36d8e0d completed March 8, 2026, 6:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69b40320a0308190b2f358fe1488ed98 completed March 13, 2026, 12:29 p.m.
NEDg Description generation batch_69b4041bc85c8190948b7e47aef0e0d0 completed March 13, 2026, 12:33 p.m.
NED2 Entity disambiguation (via description) batch_69b408778220819086935bfa9c0dd4fd completed March 13, 2026, 12:52 p.m.
Created at: March 8, 2026, 3:22 p.m.