Triple
T22553174
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St Bees railway station |
E557610
|
entity |
| Predicate | hasStationCode |
P1289
|
FINISHED |
| Object |
SBS
SBS is the National Rail station code for St Bees railway station in Cumbria, England.
|
E1543329
|
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: SBS | Statement: [St Bees railway station, hasStationCode, SBS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SBS Context triple: [St Bees railway station, hasStationCode, SBS]
-
A.
SBS
SBS is an elite British special forces unit of the Royal Navy specializing in maritime counter-terrorism, covert reconnaissance, and special operations.
-
B.
SBS
SBS is a South Korean public broadcasting organization known for its nationwide television and radio networks and popular entertainment, news, and drama programming.
-
C.
SBS
SBS is a post-nominal honorific used in Hong Kong to denote recipients of the Silver Bauhinia Star, a high-ranking government award for distinguished public service.
-
D.
SBS
SBS is the commonly used abbreviation for Santa Bárbara Sistemas, a Spanish defense contractor known for manufacturing military vehicles, weapons, and ammunition.
-
E.
SBS
SBS is the School of Biological Sciences at Nanyang Technological University, a major academic unit focused on education and research in the life sciences.
- 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: SBS Triple: [St Bees railway station, hasStationCode, SBS]
Generated description
SBS is the National Rail station code for St Bees railway station in Cumbria, England.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: SBS Target entity description: SBS is the National Rail station code for St Bees railway station in Cumbria, England.
-
A.
SBS
SBS is an elite British special forces unit of the Royal Navy specializing in maritime counter-terrorism, covert reconnaissance, and special operations.
-
B.
SBS
SBS is a South Korean public broadcasting organization known for its nationwide television and radio networks and popular entertainment, news, and drama programming.
-
C.
SBS
SBS is the commonly used abbreviation for Santa Bárbara Sistemas, a Spanish defense contractor known for manufacturing military vehicles, weapons, and ammunition.
-
D.
SBS
SBS is the School of Biological Sciences at Nanyang Technological University, a major academic unit focused on education and research in the life sciences.
-
E.
SBS
SBS is a post-nominal honorific used in Hong Kong to denote recipients of the Silver Bauhinia Star, a high-ranking government award for distinguished public service.
- 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_69e11e59db848190b4272ecd2b690ffd |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15f775d308190b35a52310e9c84f7 |
completed | April 29, 2026, 1:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0b2d6510648190aba36f0ad1bb4f81 |
completed | May 18, 2026, 3:16 p.m. |
| NEDg | Description generation | batch_6a0b364718308190937c3b7ae90ea9df |
completed | May 18, 2026, 3:54 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0b37a1ecc08190ac89e862582833a0 |
completed | May 18, 2026, 4 p.m. |
Created at: April 16, 2026, 8:52 p.m.