Triple

T1064004
Position Surface form Disambiguated ID Type / Status
Subject Ontario Science Centre E22968 entity
Predicate alsoKnownAs P39 FINISHED
Object OSC
OSC is the commonly used abbreviation for the Ontario Science Centre, a major interactive science museum and educational institution in Toronto, Canada.
 E123915 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: OSC | Statement: [Ontario Science Centre, alsoKnownAs, OSC]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: OSC
Context triple: [Ontario Science Centre, alsoKnownAs, OSC]
  • A. OSCT
    OSCT is the acronym for the UK government’s Office for Security and Counter-Terrorism, which leads national strategy and policy on counter-terrorism and security.
  • B. OSO
    OSO is the commonly used abbreviation for the Office of SIGINT Operations, a signals intelligence unit within the U.S. National Security Agency.
  • C. OC
    OC is the post-nominal designation for Officer of the Order of Canada, one of the country’s highest civilian honors recognizing outstanding achievement and service.
  • D. OSL
    OSL is the three-letter IATA airport code for Oslo Airport, Gardermoen, the main international airport serving Norway’s capital.
  • E. OIOS
    OIOS is the United Nations’ internal oversight body responsible for auditing, investigating, and evaluating the organization’s operations to ensure accountability and efficiency.
  • 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: OSC
Triple: [Ontario Science Centre, alsoKnownAs, OSC]
Generated description
OSC is the commonly used abbreviation for the Ontario Science Centre, a major interactive science museum and educational institution in Toronto, Canada.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: OSC
Target entity description: OSC is the commonly used abbreviation for the Ontario Science Centre, a major interactive science museum and educational institution in Toronto, Canada.
  • A. OSCT
    OSCT is the acronym for the UK government’s Office for Security and Counter-Terrorism, which leads national strategy and policy on counter-terrorism and security.
  • B. OSO
    OSO is the commonly used abbreviation for the Office of SIGINT Operations, a signals intelligence unit within the U.S. National Security Agency.
  • C. OC
    OC is the post-nominal designation for Officer of the Order of Canada, one of the country’s highest civilian honors recognizing outstanding achievement and service.
  • D. OSL
    OSL is the three-letter IATA airport code for Oslo Airport, Gardermoen, the main international airport serving Norway’s capital.
  • E. OIOS
    OIOS is the United Nations’ internal oversight body responsible for auditing, investigating, and evaluating the organization’s operations to ensure accountability and efficiency.
  • 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_69a493dada0481909c43649f9843ea91 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b8f85cc08190ae03ac6c84936cc5 completed March 1, 2026, 10:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac42a14b548190a796e49c545c9a9e completed March 7, 2026, 3:22 p.m.
NEDg Description generation batch_69ac4311f7f08190ae86aacb7f2103d7 completed March 7, 2026, 3:24 p.m.
NED2 Entity disambiguation (via description) batch_69ac43891ed88190a5b8b51341e98929 completed March 7, 2026, 3:26 p.m.
Created at: March 1, 2026, 7:42 p.m.