Triple

T16992776
Position Surface form Disambiguated ID Type / Status
Subject Place-des-Arts station E412233 entity
Predicate code P1537 FINISHED
Object PAD
PAD is the station code used to identify Place-des-Arts, a Montreal Metro station on the Green Line in Quebec, Canada.
E1243997 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: PAD | Statement: [Place-des-Arts station, code, PAD]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: PAD
Context triple: [Place-des-Arts station, code, PAD]
  • A. PAD
    PAD is the three-letter National Rail station code for London Paddington, a major railway terminus in central London.
  • B. PAL
    PAL is the ICAO airline designator for Philippine Airlines, the flag carrier of the Philippines.
  • C. PAL
    PAL is the European and other non-NTSC television broadcast standard that defined video format and regional compatibility for systems like the Game Boy Player.
  • D. PAT
    PAT is the National Rail station code for Patricroft railway station in Greater Manchester, England.
  • E. PAT
    PAT is the IATA airport code for Jay Prakash Narayan International Airport serving Patna, India.
  • 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: PAD
Triple: [Place-des-Arts station, code, PAD]
Generated description
PAD is the station code used to identify Place-des-Arts, a Montreal Metro station on the Green Line in Quebec, Canada.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: PAD
Target entity description: PAD is the station code used to identify Place-des-Arts, a Montreal Metro station on the Green Line in Quebec, Canada.
  • A. PAD
    PAD is the three-letter National Rail station code for London Paddington, a major railway terminus in central London.
  • B. PAL
    PAL is the ICAO airline designator for Philippine Airlines, the flag carrier of the Philippines.
  • C. PAL
    PAL is the European and other non-NTSC television broadcast standard that defined video format and regional compatibility for systems like the Game Boy Player.
  • D. PAT
    PAT is the IATA airport code for Jay Prakash Narayan International Airport serving Patna, India.
  • E. PAT
    PAT is the National Rail station code for Patricroft railway station in Greater Manchester, England.
  • 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_69d886cb581c8190ab05f4b429c9cd85 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d283d2388190a78bf8d179e83fdc completed April 18, 2026, 6:50 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00dc16fbdc819095411a056b9942c3 completed May 10, 2026, 7:27 p.m.
NEDg Description generation batch_6a00dc96a9588190b020fd7fd1deee2b completed May 10, 2026, 7:29 p.m.
NED2 Entity disambiguation (via description) batch_6a0114e04e00819093805024f8417fad completed May 10, 2026, 11:29 p.m.
Created at: April 10, 2026, 5:32 a.m.