Triple

T15243678
Position Surface form Disambiguated ID Type / Status
Subject Mo i Rana Station E364321 entity
Predicate hasStationCode P1289 FINISHED
Object MOR
MOR is the station code for Mo i Rana Station, a railway station in the town of Mo i Rana in Nordland county, Norway.
 E1145508 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: MOR | Statement: [Mo i Rana Station, hasStationCode, MOR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MOR
Context triple: [Mo i Rana Station, hasStationCode, MOR]
  • A. MOR
    MOR is the IATA airport code for Morristown Regional Airport in Tennessee, United States.
  • B. MOR
    MOR is the ICAO airline designator assigned to the former U.S. low-fare carrier Morris Air.
  • C. MOR
    MOR is the station code for Morges railway station, a key rail stop in the town of Morges in the canton of Vaud, Switzerland.
  • D. MOR
    MOR is the former Ministry of Railways of the People’s Republic of China, the government body that once oversaw the country’s railway planning, construction, and operations.
  • E. MoR
    MoR is the central government ministry in India responsible for the country’s railway network, policy, and administration.
  • 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: MOR
Triple: [Mo i Rana Station, hasStationCode, MOR]
Generated description
MOR is the station code for Mo i Rana Station, a railway station in the town of Mo i Rana in Nordland county, Norway.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MOR
Target entity description: MOR is the station code for Mo i Rana Station, a railway station in the town of Mo i Rana in Nordland county, Norway.
  • A. MOR
    MOR is the ICAO airline designator assigned to the former U.S. low-fare carrier Morris Air.
  • B. MOR
    MOR is the station code for Morges railway station, a key rail stop in the town of Morges in the canton of Vaud, Switzerland.
  • C. MOR
    MOR is the IATA airport code for Morristown Regional Airport in Tennessee, United States.
  • D. MOR
    MOR is the former Ministry of Railways of the People’s Republic of China, the government body that once oversaw the country’s railway planning, construction, and operations.
  • E. MoR
    MoR is the central government ministry in India responsible for the country’s railway network, policy, and administration.
  • 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_69d85a0dde7481908fc64d1e82d5d20d completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e007dcc33081908545ea1a1d2c19fe completed April 15, 2026, 9:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69fedd461cf08190a506aac2f0cec83a completed May 9, 2026, 7:07 a.m.
NEDg Description generation batch_69fedf6ee3f081909553078cd3e9d243 completed May 9, 2026, 7:17 a.m.
NED2 Entity disambiguation (via description) batch_69fee0016a088190ad87268e035f677e completed May 9, 2026, 7:19 a.m.
Created at: April 10, 2026, 3:13 a.m.