Triple

T4832275
Position Surface form Disambiguated ID Type / Status
Subject del.icio.us E107970 entity
Predicate subsequentOwner P12936 FINISHED
Object Science Inc. E107972 NE FINISHED

How this triple was built (2 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: Science Inc. | Statement: [del.icio.us, subsequentOwner, Science Inc.]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Science Inc.
Context triple: [del.icio.us, subsequentOwner, Science Inc.]
  • A. Science Inc. chosen
    Science Inc. is a consumer products company known for developing and marketing innovative, data-driven brands such as the meal replacement drink Soylent.
  • B. Mr. Science
    Mr. Science is a symbolic figure representing the ideals of modern scientific rationality and progress that Chinese intellectuals championed during the May Fourth Movement.
  • C. Innoventions
    Innoventions was an interactive exhibit pavilion at Epcot in Walt Disney World that showcased emerging technologies and hands-on science displays.
  • D. In the Name of Science
    In the Name of Science is the original title of Martin Gardner’s influential 1950 book critically examining pseudoscience and popular scientific misconceptions.
  • E. Sayanci
    Sayanci is a West Chadic language spoken in parts of northern Nigeria.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69bd43fac8188190803f0327190621e4 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd7162427c81908a67a07545f698ae completed March 20, 2026, 4:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69be4dd4224c8190be7568bb611f81a3 completed March 21, 2026, 7:50 a.m.
Created at: March 20, 2026, 1:24 p.m.