Triple
T20913165
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matlock railway station |
E515001
|
entity |
| Predicate | stationCode |
P1289
|
FINISHED |
| Object |
MAT
MAT is the National Rail station code for Matlock railway station in Derbyshire, England.
|
E1456381
|
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: MAT | Statement: [Matlock railway station, stationCode, MAT]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MAT Context triple: [Matlock railway station, stationCode, MAT]
-
A.
MAT
MAT is the commonly used abbreviation for the Moscow Art Theatre, a historic and influential Russian theatre company renowned for its pioneering work in modern drama and acting techniques.
-
B.
Mat
Mat is a common shortened form of the given name Matthew, often used as an informal or familiar nickname.
-
C.
MT
MT is a central character in the animated anthology series "Infinity Train," known for being a reflective, rebellious denizen of the train who struggles with questions of identity and autonomy.
-
D.
MT
MT is a widely used pseudorandom number generator algorithm known for its long period and high-quality statistical properties.
-
E.
MT
MT is the stock ticker symbol for ArcelorMittal, one of the world’s largest steel and mining companies.
- 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: MAT Triple: [Matlock railway station, stationCode, MAT]
Generated description
MAT is the National Rail station code for Matlock railway station in Derbyshire, England.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MAT Target entity description: MAT is the National Rail station code for Matlock railway station in Derbyshire, England.
-
A.
MAT
MAT is the commonly used abbreviation for the Moscow Art Theatre, a historic and influential Russian theatre company renowned for its pioneering work in modern drama and acting techniques.
-
B.
Mat
Mat is a common shortened form of the given name Matthew, often used as an informal or familiar nickname.
-
C.
MT
MT is a widely used pseudorandom number generator algorithm known for its long period and high-quality statistical properties.
-
D.
MT
MT is a central character in the animated anthology series "Infinity Train," known for being a reflective, rebellious denizen of the train who struggles with questions of identity and autonomy.
-
E.
MT
MT is the stock ticker symbol for ArcelorMittal, one of the world’s largest steel and mining companies.
- 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_69e0b4f9d5ec8190bb2bd27350ed341c |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6ec60d3288190897a087bbdd4f005 |
completed | April 21, 2026, 3:17 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0918de5fd08190a5138fdc10898c4f |
completed | May 17, 2026, 1:24 a.m. |
| NEDg | Description generation | batch_6a091993208c81908fa52d9df76bc3e4 |
completed | May 17, 2026, 1:27 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0919f58008819097e05a187ed4b3de |
completed | May 17, 2026, 1:29 a.m. |
Created at: April 16, 2026, 12:48 p.m.