Triple

T15030375
Position Surface form Disambiguated ID Type / Status
Subject Mörby centrum E378326 entity
Predicate stationCode P1289 FINISHED
Object MÖR
MÖR is the station code for Mörby centrum, a metro station on the Stockholm Metro system in Sweden.
 E1134382 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: MÖR | Statement: [Mörby centrum, stationCode, MÖR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MÖR
Context triple: [Mörby centrum, stationCode, MÖR]
  • A. Morg
    Morg is a powerful Marvel Comics supervillain who served as one of Galactus’s most ruthless and brutal heralds.
  • B. Mooz-lum
    Mooz-lum is a 2010 independent drama film that explores the experiences of a young Muslim American man struggling with identity and faith in the post-9/11 United States.
  • C. Moorer
    Moorer is a surname most notably associated with American former professional boxer and three-time world heavyweight champion Michael Moorer.
  • D. Mouresi
    Mouresi is a traditional mountain village in the Pelion region of Greece, known for its stone-built houses, lush natural surroundings, and views over the Aegean Sea.
  • E. Muher
    Muher is a Gurage language variety spoken in Ethiopia, known as one of the dialects of the Sebat Bet Gurage cluster within the Ethiosemitic language family.
  • 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: MÖR
Triple: [Mörby centrum, stationCode, MÖR]
Generated description
MÖR is the station code for Mörby centrum, a metro station on the Stockholm Metro system in Sweden.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MÖR
Target entity description: MÖR is the station code for Mörby centrum, a metro station on the Stockholm Metro system in Sweden.
  • A. Morg
    Morg is a powerful Marvel Comics supervillain who served as one of Galactus’s most ruthless and brutal heralds.
  • B. Mooz-lum
    Mooz-lum is a 2010 independent drama film that explores the experiences of a young Muslim American man struggling with identity and faith in the post-9/11 United States.
  • C. Moorer
    Moorer is a surname most notably associated with American former professional boxer and three-time world heavyweight champion Michael Moorer.
  • D. Mouresi
    Mouresi is a traditional mountain village in the Pelion region of Greece, known for its stone-built houses, lush natural surroundings, and views over the Aegean Sea.
  • E. Muher
    Muher is a Gurage language variety spoken in Ethiopia, known as one of the dialects of the Sebat Bet Gurage cluster within the Ethiosemitic language family.
  • 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_69d85cd46b2c819090d054c27787f677 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded7e2416081908dfba48d7f7b4a84 completed April 15, 2026, 12:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe9ddb46888190b1d2fe2992fc120b completed May 9, 2026, 2:37 a.m.
NEDg Description generation batch_69fe9efce5dc8190909b891c476d5291 completed May 9, 2026, 2:42 a.m.
NED2 Entity disambiguation (via description) batch_69fea2bd5d2c8190b26d2393cd8abb3e completed May 9, 2026, 2:58 a.m.
Created at: April 10, 2026, 2:59 a.m.