Triple

T19169181
Position Surface form Disambiguated ID Type / Status
Subject Toronto Western Hospital E469268 entity
Predicate alsoKnownAs P39 FINISHED
Object TWH
TWH is a major academic teaching and research hospital in downtown Toronto, renowned for its specialized care in neuroscience, musculoskeletal health, and complex patient services.
 E1361560 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: TWH | Statement: [Toronto Western Hospital, alsoKnownAs, TWH]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TWH
Context triple: [Toronto Western Hospital, alsoKnownAs, TWH]
  • A. TWH
    TWH is the National Rail station code for Tonbridge railway station in Kent, England.
  • B. WTDH
    WTDH is the radio callsign assigned to the NOAA Ship Okeanos Explorer, a U.S. research vessel dedicated to deep-ocean exploration.
  • C. HWH
    HWH is the station code for Howrah Junction, one of India’s busiest and oldest major railway terminals serving the Kolkata metropolitan area.
  • D. WHE
    WHE is the National Rail station code for Whalley railway station in Lancashire, England.
  • E. WEH
    WEH is the IATA airport code for Weihai Dashuibo Airport, a commercial airport serving the city of Weihai in Shandong Province, China.
  • 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: TWH
Triple: [Toronto Western Hospital, alsoKnownAs, TWH]
Generated description
TWH is a major academic teaching and research hospital in downtown Toronto, renowned for its specialized care in neuroscience, musculoskeletal health, and complex patient services.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TWH
Target entity description: TWH is a major academic teaching and research hospital in downtown Toronto, renowned for its specialized care in neuroscience, musculoskeletal health, and complex patient services.
  • A. TWH
    TWH is the National Rail station code for Tonbridge railway station in Kent, England.
  • B. WTDH
    WTDH is the radio callsign assigned to the NOAA Ship Okeanos Explorer, a U.S. research vessel dedicated to deep-ocean exploration.
  • C. HWH
    HWH is the station code for Howrah Junction, one of India’s busiest and oldest major railway terminals serving the Kolkata metropolitan area.
  • D. WHE
    WHE is the National Rail station code for Whalley railway station in Lancashire, England.
  • E. WEH
    WEH is the IATA airport code for Weihai Dashuibo Airport, a commercial airport serving the city of Weihai in Shandong Province, China.
  • 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_69d8dd09d5a081909ae43c286651ae5a completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5f162ac648190a5f60c6a77b68304 completed April 20, 2026, 9:26 a.m.
NED1 Entity disambiguation (via context triple) batch_6a06f2639f188190aa87c1b31b5dcb7b completed May 15, 2026, 10:16 a.m.
NEDg Description generation batch_6a06f338f504819081daeef10e629afd completed May 15, 2026, 10:19 a.m.
NED2 Entity disambiguation (via description) batch_6a06f4199a588190943d3d45536a228c completed May 15, 2026, 10:23 a.m.
Created at: April 10, 2026, 12:06 p.m.