Triple

T10115470
Position Surface form Disambiguated ID Type / Status
Subject Bobbsey Twins series E218344 entity
Predicate setting P1957 FINISHED
Object Lakeport
Lakeport is the fictional hometown where the children's mystery adventures of the Bobbsey Twins primarily take place.
 E842449 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: Lakeport | Statement: [Bobbsey Twins series, setting, Lakeport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lakeport
Context triple: [Bobbsey Twins series, setting, Lakeport]
  • A. Lewis Bay
    Lewis Bay is a sheltered coastal inlet on Cape Cod in Hyannis, Massachusetts, known for boating, beaches, and scenic waterfront views.
  • B. The Lake City
    The Lake City is the nickname of Acworth, a Georgia city known for its scenic lakes and waterfront recreation.
  • C. Lincoln Harbor
    Lincoln Harbor is a mixed-use waterfront area along the Hudson River in Weehawken, New Jersey, featuring residential buildings, offices, a marina, and transit connections to Manhattan.
  • D. Sault
    Sault is a picturesque Provençal village in southeastern France, known for its lavender fields and scenic views of Mont Ventoux.
  • E. Short Point
    Short Point is a popular coastal lookout and surf beach area in Merimbula, New South Wales, known for its scenic ocean views and whale-watching opportunities.
  • 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: Lakeport
Triple: [Bobbsey Twins series, setting, Lakeport]
Generated description
Lakeport is the fictional hometown where the children's mystery adventures of the Bobbsey Twins primarily take place.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lakeport
Target entity description: Lakeport is the fictional hometown where the children's mystery adventures of the Bobbsey Twins primarily take place.
  • A. Lewis Bay
    Lewis Bay is a sheltered coastal inlet on Cape Cod in Hyannis, Massachusetts, known for boating, beaches, and scenic waterfront views.
  • B. The Lake City
    The Lake City is the nickname of Acworth, a Georgia city known for its scenic lakes and waterfront recreation.
  • C. Lincoln Harbor
    Lincoln Harbor is a mixed-use waterfront area along the Hudson River in Weehawken, New Jersey, featuring residential buildings, offices, a marina, and transit connections to Manhattan.
  • D. Sault
    Sault is a picturesque Provençal village in southeastern France, known for its lavender fields and scenic views of Mont Ventoux.
  • E. Short Point
    Short Point is a popular coastal lookout and surf beach area in Merimbula, New South Wales, known for its scenic ocean views and whale-watching opportunities.
  • 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_69ca83da93fc8190b54e44bc2b34857c completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cdd161831c81908bb3c77caa7c3ce1 completed April 2, 2026, 2:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2cc2b00488190acca51a797beed45 completed April 5, 2026, 8:55 p.m.
NEDg Description generation batch_69d2cda6452c81908d67ea322da3cf70 completed April 5, 2026, 9:01 p.m.
NED2 Entity disambiguation (via description) batch_69d2ce6da82081908ca6b3621971ca9a completed April 5, 2026, 9:04 p.m.
Created at: March 30, 2026, 9:04 p.m.