Triple

T3565956
Position Surface form Disambiguated ID Type / Status
Subject Davisville station E75447 entity
Predicate code P1537 FINISHED
Object DAV
DAV is the station code used to identify Davisville station in the Toronto subway system.
E369417 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: DAV | Statement: [Davisville station, code, DAV]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: DAV
Context triple: [Davisville station, code, DAV]
  • A. D-a-v-e
    D-a-v-e is a stylized spelling of the common given name "Dave," typically a diminutive of "David."
  • B. DASA
    DASA (Deutsche Aerospace AG) was a major German aerospace and defense company that became a core component of the later European aerospace giant Airbus Group.
  • C. DAP
    DAP (Directory Access Protocol) is an early X.500 directory service protocol that provided a complex, OSI-based method for accessing and managing directory information before being largely replaced by LDAP.
  • D. DAP
    DAP was the abbreviation for the German Workers' Party, a far-right nationalist and anti-Semitic political party in post–World War I Germany that later evolved into the Nazi Party.
  • E. DA
    DA is the official abbreviation for the United States Department of the Army, the federal agency responsible for organizing, training, and equipping the U.S. Army.
  • 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: DAV
Triple: [Davisville station, code, DAV]
Generated description
DAV is the station code used to identify Davisville station in the Toronto subway system.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: DAV
Target entity description: DAV is the station code used to identify Davisville station in the Toronto subway system.
  • A. D-a-v-e
    D-a-v-e is a stylized spelling of the common given name "Dave," typically a diminutive of "David."
  • B. DASA
    DASA (Deutsche Aerospace AG) was a major German aerospace and defense company that became a core component of the later European aerospace giant Airbus Group.
  • C. DAP
    DAP (Directory Access Protocol) is an early X.500 directory service protocol that provided a complex, OSI-based method for accessing and managing directory information before being largely replaced by LDAP.
  • D. DAP
    DAP was the abbreviation for the German Workers' Party, a far-right nationalist and anti-Semitic political party in post–World War I Germany that later evolved into the Nazi Party.
  • E. DA
    DA is the official abbreviation for the United States Department of the Army, the federal agency responsible for organizing, training, and equipping the U.S. Army.
  • 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_69ad85d512708190829c8b2d3a2ccfb8 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc0a8f6288190928479f5bea32245 completed March 8, 2026, 6:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69b3bbacbb1081908fc57168a8fc3ade completed March 13, 2026, 7:24 a.m.
NEDg Description generation batch_69b3bf78d6a881908d5bcc4ae50a76e5 completed March 13, 2026, 7:40 a.m.
NED2 Entity disambiguation (via description) batch_69b3f5adac0481908b9053585c317be0 completed March 13, 2026, 11:31 a.m.
Created at: March 8, 2026, 3:21 p.m.