Triple

T13510238
Position Surface form Disambiguated ID Type / Status
Subject Bloemendaal railway station E321119 entity
Predicate stationCode P1289 FINISHED
Object Bdl
Bdl is the station code for Bloemendaal railway station in the Netherlands.
 E1044025 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: Bdl | Statement: [Bloemendaal railway station, stationCode, Bdl]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bdl
Context triple: [Bloemendaal railway station, stationCode, Bdl]
  • A. BDL
    BDL is the commonly used abbreviation for Banque du Liban, the central bank of Lebanon responsible for the country’s monetary policy and financial stability.
  • B. BDL
    BDL is the three-letter IATA airport code for Bradley International Airport, a major commercial airport serving the Hartford–Springfield region in the northeastern United States.
  • C. BD
    BD is the currency symbol used to denote the Bahraini dinar, the official monetary unit of Bahrain.
  • D. BD
    BD is the UK postcode area covering Bradford and surrounding parts of West Yorkshire.
  • E. BD
    BD is the station code used to identify Bandung railway station in Indonesia’s rail network.
  • 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: Bdl
Triple: [Bloemendaal railway station, stationCode, Bdl]
Generated description
Bdl is the station code for Bloemendaal railway station in the Netherlands.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bdl
Target entity description: Bdl is the station code for Bloemendaal railway station in the Netherlands.
  • A. BDL
    BDL is the commonly used abbreviation for Banque du Liban, the central bank of Lebanon responsible for the country’s monetary policy and financial stability.
  • B. BDL
    BDL is the three-letter IATA airport code for Bradley International Airport, a major commercial airport serving the Hartford–Springfield region in the northeastern United States.
  • C. BD
    BD is the UK postcode area covering Bradford and surrounding parts of West Yorkshire.
  • D. BD
    BD is the currency symbol used to denote the Bahraini dinar, the official monetary unit of Bahrain.
  • E. BD
    BD is the station code used to identify Bandung railway station in Indonesia’s rail network.
  • 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_69d807629d6c8190998f1b9bb12d2ed0 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbaf86a6208190be8c18f7a0158f23 completed April 12, 2026, 2:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69f75490291c8190b5985d8c90ef1af6 completed May 3, 2026, 1:58 p.m.
NEDg Description generation batch_69f7556329648190be791afdd197b08c completed May 3, 2026, 2:02 p.m.
NED2 Entity disambiguation (via description) batch_69f755c52c648190a4912725ce65ff04 completed May 3, 2026, 2:03 p.m.
Created at: April 9, 2026, 9:43 p.m.