Triple

T3934933
Position Surface form Disambiguated ID Type / Status
Subject Deanwood station E90885 entity
Predicate code P1537 FINISHED
Object D10
D10 is the station code for Deanwood, a stop on Washington, D.C.’s Metrorail system.
 E399754 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: D10 | Statement: [Deanwood station, code, D10]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: D10
Context triple: [Deanwood station, code, D10]
  • A. D-1
    D-1 was a pioneering early Spacelab mission that helped demonstrate and validate the European-built laboratory’s capabilities for conducting scientific research in space aboard the Space Shuttle.
  • B. T10
    T10 is a technical committee under INCITS responsible for developing standards for SCSI (Small Computer System Interface) and related storage interfaces.
  • C. D16
    D16 was the pennant number assigned to HMS Ivanhoe, a British Royal Navy I-class destroyer that served during World War II.
  • D. O-10
    O-10 is the highest pay grade for four-star flag and general officers in the U.S. Armed Forces, including admirals and full generals.
  • E. D5
    D5 is a commuter rail line within the Moscow Central Diameters network that serves as one of the key cross-city routes in the Moscow metropolitan area.
  • 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: D10
Triple: [Deanwood station, code, D10]
Generated description
D10 is the station code for Deanwood, a stop on Washington, D.C.’s Metrorail system.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: D10
Target entity description: D10 is the station code for Deanwood, a stop on Washington, D.C.’s Metrorail system.
  • A. D-1
    D-1 was a pioneering early Spacelab mission that helped demonstrate and validate the European-built laboratory’s capabilities for conducting scientific research in space aboard the Space Shuttle.
  • B. T10
    T10 is a technical committee under INCITS responsible for developing standards for SCSI (Small Computer System Interface) and related storage interfaces.
  • C. D16
    D16 was the pennant number assigned to HMS Ivanhoe, a British Royal Navy I-class destroyer that served during World War II.
  • D. O-10
    O-10 is the highest pay grade for four-star flag and general officers in the U.S. Armed Forces, including admirals and full generals.
  • E. D5
    D5 is a commuter rail line within the Moscow Central Diameters network that serves as one of the key cross-city routes in the Moscow metropolitan area.
  • 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_69aed95f26e0819094b0e71974543a19 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeedcbf0188190a5e828707a77752a completed March 9, 2026, 3:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5288b7538819084936489226dd31f completed March 14, 2026, 9:21 a.m.
NEDg Description generation batch_69b529a1486881908ff348558199232b completed March 14, 2026, 9:25 a.m.
NED2 Entity disambiguation (via description) batch_69b52a43c6f081908366d9848728f98a completed March 14, 2026, 9:28 a.m.
Created at: March 9, 2026, 3:23 p.m.