Triple
T5588572
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Knivsta railway station |
E146817
|
entity |
| Predicate | hasStationCode |
P1289
|
FINISHED |
| Object |
Knv
Knv is the station code for Knivsta railway station in Sweden.
|
E536688
|
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: Knv | Statement: [Knivsta railway station, hasStationCode, Knv]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Knv Context triple: [Knivsta railway station, hasStationCode, Knv]
-
A.
DKNVS
DKNVS is the abbreviation for the Royal Norwegian Society of Sciences and Letters, one of Norway’s oldest and most prestigious learned societies dedicated to the advancement of science and scholarship.
-
B.
KNA
KNA is the three-letter ISO 3166-1 alpha-3 country code assigned to Saint Kitts and Nevis.
-
C.
KNF
KNF is the IATA airport code for RAF Marham, a Royal Air Force station in Norfolk, England.
-
D.
KN
KN is the IATA airline designator assigned to China United Airlines, a Chinese domestic carrier based in Beijing.
-
E.
KNB
KNB is the abbreviation for Khazanah Nasional, Malaysia’s sovereign wealth fund and strategic investment arm of the government.
- 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: Knv Triple: [Knivsta railway station, hasStationCode, Knv]
Generated description
Knv is the station code for Knivsta railway station in Sweden.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Knv Target entity description: Knv is the station code for Knivsta railway station in Sweden.
-
A.
DKNVS
DKNVS is the abbreviation for the Royal Norwegian Society of Sciences and Letters, one of Norway’s oldest and most prestigious learned societies dedicated to the advancement of science and scholarship.
-
B.
KNA
KNA is the three-letter ISO 3166-1 alpha-3 country code assigned to Saint Kitts and Nevis.
-
C.
KNF
KNF is the IATA airport code for RAF Marham, a Royal Air Force station in Norfolk, England.
-
D.
KN
KN is the IATA airline designator assigned to China United Airlines, a Chinese domestic carrier based in Beijing.
-
E.
KNB
KNB is the abbreviation for Khazanah Nasional, Malaysia’s sovereign wealth fund and strategic investment arm of the government.
- 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_69c009036c408190981a8d690b679b67 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c0209e892c8190b936a05ef2a14d36 |
completed | March 22, 2026, 5:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c04d2f8710819094f5d052b767b9a6 |
completed | March 22, 2026, 8:12 p.m. |
| NEDg | Description generation | batch_69c04e88680c8190845723f52c060fb7 |
completed | March 22, 2026, 8:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c04f7856848190a835c3ee0a32f649 |
completed | March 22, 2026, 8:22 p.m. |
Created at: March 22, 2026, 3:38 p.m.