Triple

T6661777
Position Surface form Disambiguated ID Type / Status
Subject Dalmeny railway station E151492 entity
Predicate stationCode P1289 FINISHED
Object DAM
DAM is the National Rail station code used to identify Dalmeny railway station in Scotland’s rail network.
 E608887 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: DAM | Statement: [Dalmeny railway station, stationCode, DAM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: DAM
Context triple: [Dalmeny railway station, stationCode, DAM]
  • A. DAM
    DAM is the three-letter IATA airport code for Damascus International Airport, the main airport serving Syria’s capital city.
  • B. DPM
    DPM is the abbreviation for the División de Policía Militar, a military police division responsible for law enforcement and security duties within a nation's armed forces.
  • C. DIT
    DIT is the South Australian government department responsible for planning, developing, and managing the state’s transport systems and infrastructure.
  • D. DAS
    DAS is the acronym for the Defense Attache Service, the U.S. military organization that manages defense attachés and military diplomatic representation at American embassies worldwide.
  • E. DAL
    DAL is the standard three-letter abbreviation used for the NBA team Dallas Mavericks.
  • 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: DAM
Triple: [Dalmeny railway station, stationCode, DAM]
Generated description
DAM is the National Rail station code used to identify Dalmeny railway station in Scotland’s rail network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: DAM
Target entity description: DAM is the National Rail station code used to identify Dalmeny railway station in Scotland’s rail network.
  • A. DAM
    DAM is the three-letter IATA airport code for Damascus International Airport, the main airport serving Syria’s capital city.
  • B. DPM
    DPM is the abbreviation for the División de Policía Militar, a military police division responsible for law enforcement and security duties within a nation's armed forces.
  • C. DIT
    DIT is the South Australian government department responsible for planning, developing, and managing the state’s transport systems and infrastructure.
  • D. DAS
    DAS is the acronym for the Defense Attache Service, the U.S. military organization that manages defense attachés and military diplomatic representation at American embassies worldwide.
  • E. DAL
    DAL is the standard three-letter abbreviation used for the NBA team Dallas Mavericks.
  • 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_69c687f5fac48190a09e4838d9c6b45d completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6b097e0e481909251443f9ce0b85a completed March 27, 2026, 4:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6ef0a0c208190ac6a309bfb2e4e4b completed March 27, 2026, 8:56 p.m.
NEDg Description generation batch_69c6f0a3f0b481908dfe70d626277e8f completed March 27, 2026, 9:03 p.m.
NED2 Entity disambiguation (via description) batch_69c6f1a3995c8190b22766356b6e6bf8 completed March 27, 2026, 9:07 p.m.
Created at: March 27, 2026, 2:02 p.m.