Triple
T21118911
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dorking Deepdene railway station |
E520372
|
entity |
| Predicate | stationCode |
P1289
|
FINISHED |
| Object |
DPD
DPD is the three-letter National Rail station code assigned to Dorking Deepdene railway station in Surrey, England.
|
E1467990
|
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: DPD | Statement: [Dorking Deepdene railway station, stationCode, DPD]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DPD Context triple: [Dorking Deepdene railway station, stationCode, DPD]
-
A.
DPD
DPD is the commonly used abbreviation for Indonesia’s Regional Representative Council, the upper house of its national legislature.
-
B.
DPD
DPD is the commonly used abbreviation for the "Diccionario panhispánico de dudas," a comprehensive reference work by the Royal Spanish Academy that clarifies usage, grammar, and style questions across the Spanish-speaking world.
-
C.
DPDgroup
DPDgroup is a major international parcel delivery and logistics company operating across Europe and beyond under brands such as DPD, Chronopost, and SEUR.
-
D.
DPO
DPO is the IATA airport code for Devonport Airport in Tasmania, Australia.
-
E.
DPP
DPP is the Maryland state agency responsible for supervising individuals on parole and probation and supporting their reintegration into the community.
- 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: DPD Triple: [Dorking Deepdene railway station, stationCode, DPD]
Generated description
DPD is the three-letter National Rail station code assigned to Dorking Deepdene railway station in Surrey, England.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: DPD Target entity description: DPD is the three-letter National Rail station code assigned to Dorking Deepdene railway station in Surrey, England.
-
A.
DPD
DPD is the commonly used abbreviation for the "Diccionario panhispánico de dudas," a comprehensive reference work by the Royal Spanish Academy that clarifies usage, grammar, and style questions across the Spanish-speaking world.
-
B.
DPD
DPD is the commonly used abbreviation for Indonesia’s Regional Representative Council, the upper house of its national legislature.
-
C.
DPDgroup
DPDgroup is a major international parcel delivery and logistics company operating across Europe and beyond under brands such as DPD, Chronopost, and SEUR.
-
D.
DPO
DPO is the IATA airport code for Devonport Airport in Tasmania, Australia.
-
E.
DPP
DPP is the Maryland state agency responsible for supervising individuals on parole and probation and supporting their reintegration into the community.
- 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_69e0b50a623881909c0bbaf4f2c055e7 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7223176c48190bfbaea41c2209a15 |
completed | April 21, 2026, 7:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0965e7c4e88190acf4e6d4402ccbb0 |
completed | May 17, 2026, 6:53 a.m. |
| NEDg | Description generation | batch_6a09670987f0819086b021581db69c85 |
completed | May 17, 2026, 6:58 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0967cefab08190b01e2c897f081105 |
completed | May 17, 2026, 7:01 a.m. |
Created at: April 16, 2026, 2:55 p.m.