Triple

T8709409
Position Surface form Disambiguated ID Type / Status
Subject London Borough of Barking and Dagenham E206735 entity
Predicate postalCodeArea P920 FINISHED
Object RM
RM is a UK postcode area in east London and parts of Essex, covering districts such as Romford and surrounding suburbs.
 E753637 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: RM | Statement: [London Borough of Barking and Dagenham, postalCodeArea, RM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: RM
Context triple: [London Borough of Barking and Dagenham, postalCodeArea, RM]
  • A. RM
    RM is the currency symbol that was used to denote the German Reichsmark, the former official currency of Germany from 1924 to 1948.
  • B. RM
    RM is a South Korean rapper, songwriter, and leader of the globally renowned K-pop group BTS.
  • C. RB
    RB is the abbreviation for CERN’s Research Board, the committee responsible for overseeing and approving the laboratory’s scientific research program.
  • D. RK
    RK is the vehicle registration code used for the town of Ružomberok in northern Slovakia.
  • E. RK
    RK is the commonly used abbreviation for the Riigikogu, the unicameral national parliament of Estonia.
  • 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: RM
Triple: [London Borough of Barking and Dagenham, postalCodeArea, RM]
Generated description
RM is a UK postcode area in east London and parts of Essex, covering districts such as Romford and surrounding suburbs.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: RM
Target entity description: RM is a UK postcode area in east London and parts of Essex, covering districts such as Romford and surrounding suburbs.
  • A. RM
    RM is the currency symbol that was used to denote the German Reichsmark, the former official currency of Germany from 1924 to 1948.
  • B. RM
    RM is a South Korean rapper, songwriter, and leader of the globally renowned K-pop group BTS.
  • C. RB
    RB is the abbreviation for CERN’s Research Board, the committee responsible for overseeing and approving the laboratory’s scientific research program.
  • D. RK
    RK is the vehicle registration code used for the town of Ružomberok in northern Slovakia.
  • E. RK
    RK is the commonly used abbreviation for the Riigikogu, the unicameral national parliament of Estonia.
  • 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_69ca835645e881908f00e3c8b51da81d completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5c2e9c688190aceefaa2c3b7d7bd completed March 31, 2026, 11:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf28b78e90819098ab1d4877ab88fe completed April 3, 2026, 2:40 a.m.
NEDg Description generation batch_69cf2bd14c3c8190b43840ee57cca22c completed April 3, 2026, 2:54 a.m.
NED2 Entity disambiguation (via description) batch_69cf2cb3c4308190971fb3d25064f205 completed April 3, 2026, 2:57 a.m.
Created at: March 30, 2026, 6:35 p.m.