Triple

T12638519
Position Surface form Disambiguated ID Type / Status
Subject Moor Park E301828 entity
Predicate hasStationCode P1289 FINISHED
Object MOP
MOP is the National Rail station code for Moor Park railway station in Hertfordshire, England.
 E994711 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: MOP | Statement: [Moor Park, hasStationCode, MOP]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MOP
Context triple: [Moor Park, hasStationCode, MOP]
  • A. MOP
    MOP is the ISO 4217 currency code for the Macanese pataca, the official currency of Macau.
  • B. MOP
    MOP is the IATA airport code for Mount Pleasant Municipal Airport in Michigan, United States.
  • C. MOPITT
    MOPITT is a satellite instrument aboard NASA's Terra spacecraft designed to measure global distributions of atmospheric carbon monoxide and methane for climate and air quality research.
  • D. JMO
    JMO is the IATA airport code for Jomsom Airport, a domestic airport serving the town of Jomsom in Nepal’s Mustang region.
  • E. IMO
    IMO is a specialized United Nations agency responsible for regulating international shipping and promoting maritime safety, security, and environmental protection.
  • 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: MOP
Triple: [Moor Park, hasStationCode, MOP]
Generated description
MOP is the National Rail station code for Moor Park railway station in Hertfordshire, England.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MOP
Target entity description: MOP is the National Rail station code for Moor Park railway station in Hertfordshire, England.
  • A. MOP
    MOP is the ISO 4217 currency code for the Macanese pataca, the official currency of Macau.
  • B. MOP
    MOP is the IATA airport code for Mount Pleasant Municipal Airport in Michigan, United States.
  • C. MOPITT
    MOPITT is a satellite instrument aboard NASA's Terra spacecraft designed to measure global distributions of atmospheric carbon monoxide and methane for climate and air quality research.
  • D. JMO
    JMO is the IATA airport code for Jomsom Airport, a domestic airport serving the town of Jomsom in Nepal’s Mustang region.
  • E. IMO
    IMO is a specialized United Nations agency responsible for regulating international shipping and promoting maritime safety, security, and environmental protection.
  • 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_69d7bdec9f9c8190b4bac675b7588211 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d961499de08190bdba66ca40b021be completed April 10, 2026, 8:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69f668754acc8190b5585dbd35387867 completed May 2, 2026, 9:11 p.m.
NEDg Description generation batch_69f6697d8ac88190b4ead9ce47f3a705 completed May 2, 2026, 9:15 p.m.
NED2 Entity disambiguation (via description) batch_69f66a2da60881909b0a689821456bb4 completed May 2, 2026, 9:18 p.m.
Created at: April 9, 2026, 5:16 p.m.