Triple

T14773940
Position Surface form Disambiguated ID Type / Status
Subject Veendam railway station E347204 entity
Predicate hasStationCode P1289 FINISHED
Object Vdm
Vdm is the official station code used to identify Veendam railway station in the Netherlands.
E1119504 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: Vdm | Statement: [Veendam railway station, hasStationCode, Vdm]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vdm
Context triple: [Veendam railway station, hasStationCode, Vdm]
  • A. Vdm
    Vdm is the official station code for Van der Madeweg, a metro station in Amsterdam, Netherlands.
  • B. VDP
    VDP is a networking protocol used to automatically discover and configure virtual devices or ports in virtualized environments.
  • C. VDV
    VDV is the elite airborne branch of Russia’s armed forces, known for rapid-deployment paratrooper and air-assault operations.
  • D. Fresh VDM
    Fresh VDM is a Nigerian music producer best known for crafting Afropop and Afrobeats hits, including work on Davido’s acclaimed album "A Good Time."
  • E. VDH
    VDH is the state public health agency responsible for protecting and promoting the health of residents in Virginia.
  • 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: Vdm
Triple: [Veendam railway station, hasStationCode, Vdm]
Generated description
Vdm is the official station code used to identify Veendam railway station in the Netherlands.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Vdm
Target entity description: Vdm is the official station code used to identify Veendam railway station in the Netherlands.
  • A. Vdm
    Vdm is the official station code for Van der Madeweg, a metro station in Amsterdam, Netherlands.
  • B. VDP
    VDP is a networking protocol used to automatically discover and configure virtual devices or ports in virtualized environments.
  • C. VDV
    VDV is the elite airborne branch of Russia’s armed forces, known for rapid-deployment paratrooper and air-assault operations.
  • D. Fresh VDM
    Fresh VDM is a Nigerian music producer best known for crafting Afropop and Afrobeats hits, including work on Davido’s acclaimed album "A Good Time."
  • E. VDH
    VDH is the state public health agency responsible for protecting and promoting the health of residents in Virginia.
  • 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_69d822e9b9e08190bedcc31a163fda82 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec81485e08190be35baafcf22b6f2 completed April 14, 2026, 11:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe0cfd26fc81909fba39c8705437ed completed May 8, 2026, 4:19 p.m.
NEDg Description generation batch_69fe17fc37ec8190b2e9c786a5e7843e completed May 8, 2026, 5:06 p.m.
NED2 Entity disambiguation (via description) batch_69fe18786294819080ce5ee0d8af00c9 completed May 8, 2026, 5:08 p.m.
Created at: April 10, 2026, 1:31 a.m.