Triple

T16978122
Position Surface form Disambiguated ID Type / Status
Subject Siene E411866 entity
Predicate alternateNameOf P39 FINISHED
Object Swenett
Swenett is the ancient Egyptian town known to the Greeks as Syene (modern Aswan), a strategic frontier city and important trading center at Egypt’s southern border.
 E84747 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: Swenett | Statement: [Siene, alternateNameOf, Swenett]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Swenett
Context triple: [Siene, alternateNameOf, Swenett]
  • A. Swenett
    Swenett is the ancient Egyptian city known today as Aswan, a historic frontier town on the Nile near Egypt’s southern border.
  • B. Swineford
    Swineford is a small settlement in South Gloucestershire, England, situated near the River Avon between Bristol and Bath.
  • C. Scarphe
    Scarphe is a figure from Greek mythology known primarily as the wife of Aeson, the father of the hero Jason.
  • D. Sullane
    The Sullane is a river in County Cork, Ireland, that flows through the town of Macroom before joining the River Lee.
  • E. Elswit
    Elswit is the surname of Robert Elswit, an acclaimed American cinematographer known for his work on films such as "There Will Be Blood."
  • 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: Swenett
Triple: [Siene, alternateNameOf, Swenett]
Generated description
Swenett is the ancient Egyptian town known to the Greeks as Syene (modern Aswan), a strategic frontier city and important trading center at Egypt’s southern border.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Swenett
Target entity description: Swenett is the ancient Egyptian town known to the Greeks as Syene (modern Aswan), a strategic frontier city and important trading center at Egypt’s southern border.
  • A. Swenett chosen
    Swenett is the ancient Egyptian city known today as Aswan, a historic frontier town on the Nile near Egypt’s southern border.
  • B. Swineford
    Swineford is a small settlement in South Gloucestershire, England, situated near the River Avon between Bristol and Bath.
  • C. Scarphe
    Scarphe is a figure from Greek mythology known primarily as the wife of Aeson, the father of the hero Jason.
  • D. Sullane
    The Sullane is a river in County Cork, Ireland, that flows through the town of Macroom before joining the River Lee.
  • E. Elswit
    Elswit is the surname of Robert Elswit, an acclaimed American cinematographer known for his work on films such as "There Will Be Blood."
  • 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_69d886ca8f348190812768ea8d5055ce completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d185a9408190a991bf8a1ef694f0 completed April 18, 2026, 6:46 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00d477f7ec81909f1f0243004c9050 completed May 10, 2026, 6:54 p.m.
NEDg Description generation batch_6a00d5503be88190ac15a327ff3782ec completed May 10, 2026, 6:58 p.m.
NED2 Entity disambiguation (via description) batch_6a00d66e450c8190ae0befd3d7875ed8 completed May 10, 2026, 7:03 p.m.
Created at: April 10, 2026, 5:32 a.m.