Triple

T8195408
Position Surface form Disambiguated ID Type / Status
Subject John Seely Brown E191417 entity
Predicate alternateName P39 FINISHED
Object JSB
JSB is the commonly used abbreviation for John Seely Brown, an American researcher and former chief scientist at Xerox PARC known for his work on organizational learning, innovation, and the social aspects of technology.
 E718414 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: JSB | Statement: [John Seely Brown, alternateName, JSB]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: JSB
Context triple: [John Seely Brown, alternateName, JSB]
  • A. JS21
    JS21 is the station code assigned to Ikebukuro Station on Japan’s JR rail network.
  • B. Jkb
    Jkb is the station code for Jakobsberg railway station in Sweden.
  • C. JBAB
    JBAB is the commonly used abbreviation for Joint Base Anacostia–Bolling, a major U.S. military installation located in Washington, D.C.
  • D. JSBC
    JSBC is the commonly used abbreviation for the Jersey Shore BlueClaws, a Minor League Baseball team based in New Jersey.
  • E. JS Kaga
    JS Kaga is a Japanese Maritime Self-Defense Force warship, the second vessel of the Izumo-class designed primarily for anti-submarine warfare and helicopter operations.
  • 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: JSB
Triple: [John Seely Brown, alternateName, JSB]
Generated description
JSB is the commonly used abbreviation for John Seely Brown, an American researcher and former chief scientist at Xerox PARC known for his work on organizational learning, innovation, and the social aspects of technology.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: JSB
Target entity description: JSB is the commonly used abbreviation for John Seely Brown, an American researcher and former chief scientist at Xerox PARC known for his work on organizational learning, innovation, and the social aspects of technology.
  • A. JS21
    JS21 is the station code assigned to Ikebukuro Station on Japan’s JR rail network.
  • B. Jkb
    Jkb is the station code for Jakobsberg railway station in Sweden.
  • C. JBAB
    JBAB is the commonly used abbreviation for Joint Base Anacostia–Bolling, a major U.S. military installation located in Washington, D.C.
  • D. JSBC
    JSBC is the commonly used abbreviation for the Jersey Shore BlueClaws, a Minor League Baseball team based in New Jersey.
  • E. JS Kaga
    JS Kaga is a Japanese Maritime Self-Defense Force warship, the second vessel of the Izumo-class designed primarily for anti-submarine warfare and helicopter operations.
  • 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_69ca82c6e9548190a4c5ca14516e4417 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb5c20fbd08190b9966e3c967e9c71 completed March 31, 2026, 5:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69ccedaab8848190877fbe2de9b83957 completed April 1, 2026, 10:04 a.m.
NEDg Description generation batch_69ccf1b706f08190993f4a75eac5f49c completed April 1, 2026, 10:21 a.m.
NED2 Entity disambiguation (via description) batch_69cd059457788190a900402ee4cd50d5 completed April 1, 2026, 11:46 a.m.
Created at: March 30, 2026, 5:42 p.m.