Triple
T13973095
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Milton Keynes Lightning |
E336112
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object |
MKL
MKL is a professional ice hockey team based in Milton Keynes, England, competing in the British ice hockey league system.
|
E1071942
|
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: MKL | Statement: [Milton Keynes Lightning, abbreviation, MKL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MKL Context triple: [Milton Keynes Lightning, abbreviation, MKL]
-
A.
MVL
MVL is the three-letter National Rail station code for Malvern Link railway station in Worcestershire, England.
-
B.
MVL
MVL is the abbreviation for the Man Vehicle Laboratory, a research lab focused on human factors and human–machine interaction in aerospace and related fields.
-
C.
KMK
KMK is the central coordinating body of Germany’s state education and cultural ministers, responsible for harmonizing policies across the federal states.
-
D.
M-K
M-K is the commonly used abbreviation for Morrison-Knudsen, a major American engineering and construction company known for large-scale infrastructure projects.
-
E.
MKS
MKS is the standard abbreviation for the academic journal "Marketing Science," which publishes research on quantitative and analytical approaches to marketing.
- 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: MKL Triple: [Milton Keynes Lightning, abbreviation, MKL]
Generated description
MKL is a professional ice hockey team based in Milton Keynes, England, competing in the British ice hockey league system.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MKL Target entity description: MKL is a professional ice hockey team based in Milton Keynes, England, competing in the British ice hockey league system.
-
A.
MVL
MVL is the abbreviation for the Man Vehicle Laboratory, a research lab focused on human factors and human–machine interaction in aerospace and related fields.
-
B.
MVL
MVL is the three-letter National Rail station code for Malvern Link railway station in Worcestershire, England.
-
C.
KMK
KMK is the central coordinating body of Germany’s state education and cultural ministers, responsible for harmonizing policies across the federal states.
-
D.
M-K
M-K is the commonly used abbreviation for Morrison-Knudsen, a major American engineering and construction company known for large-scale infrastructure projects.
-
E.
MKS
MKS is the standard abbreviation for the academic journal "Marketing Science," which publishes research on quantitative and analytical approaches to marketing.
- 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_69d81c61f3508190aaf2ca0dc0002c59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e8fd6d48190a157eae8df3a2f3a |
completed | April 14, 2026, 12:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fba1df334c8190a3d65198cc3d11f6 |
completed | May 6, 2026, 8:17 p.m. |
| NEDg | Description generation | batch_69fba5918348819084fa4235eec6eee0 |
completed | May 6, 2026, 8:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fba6b5e4f4819088e8a0629e17e4cc |
completed | May 6, 2026, 8:38 p.m. |
Created at: April 9, 2026, 10:18 p.m.