Triple

T13197316
Position Surface form Disambiguated ID Type / Status
Subject Dr. Samuel Hape E314146 entity
Predicate familyName P18 FINISHED
Object Hape
Hape is a surname that may refer to various individuals, including Dr. Samuel Hape.
 E1026330 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: Hape | Statement: [Dr. Samuel Hape, familyName, Hape]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hape
Context triple: [Dr. Samuel Hape, familyName, Hape]
  • A. Hauerland
    Hauerland was a historical German-speaking enclave in central Slovakia, settled by Carpathian Germans in the Middle Ages.
  • B. Haps
    Haps is a village in the Dutch province of North Brabant, now part of the municipality of Land van Cuijk.
  • C. Pluzz
    Pluzz was France Télévisions’ former online catch-up TV and streaming platform, later succeeded by france.tv.
  • D. Hama
    Hama is a major city in west-central Syria, historically known for its ancient waterwheels (norias) on the Orontes River and its role as an important agricultural and industrial center.
  • E. Hapton
    Hapton is a village and civil parish in Lancashire, England, situated within the Borough of Burnley.
  • 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: Hape
Triple: [Dr. Samuel Hape, familyName, Hape]
Generated description
Hape is a surname that may refer to various individuals, including Dr. Samuel Hape.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hape
Target entity description: Hape is a surname that may refer to various individuals, including Dr. Samuel Hape.
  • A. Hauerland
    Hauerland was a historical German-speaking enclave in central Slovakia, settled by Carpathian Germans in the Middle Ages.
  • B. Haps
    Haps is a village in the Dutch province of North Brabant, now part of the municipality of Land van Cuijk.
  • C. Pluzz
    Pluzz was France Télévisions’ former online catch-up TV and streaming platform, later succeeded by france.tv.
  • D. Hama
    Hama is a major city in west-central Syria, historically known for its ancient waterwheels (norias) on the Orontes River and its role as an important agricultural and industrial center.
  • E. Hapton
    Hapton is a village and civil parish in Lancashire, England, situated within the Borough of Burnley.
  • 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_69d806ae1e08819090d95bfe1538cc17 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98c64290881909759ef3a281b6a68 completed April 10, 2026, 11:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6f605a48c81909373fcd9dd896b3d completed May 3, 2026, 7:15 a.m.
NEDg Description generation batch_69f6f6e10f2481909b405169dd7e5cf9 completed May 3, 2026, 7:18 a.m.
NED2 Entity disambiguation (via description) batch_69f6f73b301881909d792dfebd2e468f completed May 3, 2026, 7:20 a.m.
Created at: April 9, 2026, 9:16 p.m.