Triple
T2092386
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robin Milner |
E32698
|
entity |
| Predicate | knownFor |
P22
|
FINISHED |
| Object | ML programming language |
E131757
|
NE FINISHED |
How this triple was built (2 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: ML programming language | Statement: [Robin Milner, knownFor, ML programming language]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ML programming language Context triple: [Robin Milner, knownFor, ML programming language]
-
A.
M language
M language is a functional, case-sensitive data mashup and transformation language used primarily in Microsoft Power Query for importing, shaping, and combining data from diverse sources.
-
B.
ML
chosen
ML is a statically typed functional programming language developed at the University of Edinburgh, known for pioneering features like type inference, pattern matching, and modules that strongly influenced later languages such as Elm, Haskell, and OCaml.
-
C.
ML
ML is the postcode area in central Scotland that covers Motherwell and surrounding towns.
-
D.
Mono language
Mono language is a Native American Uto-Aztecan language traditionally spoken by the Mono people of eastern California.
-
E.
ML.NET
ML.NET is an open-source, cross-platform machine learning framework for .NET developers to build and integrate custom ML models into .NET applications.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69a885eba0708190999696a45cbec816 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69abba774ca881909f83cf65ffeb24bb |
completed | March 7, 2026, 5:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae2746fb3481909e0b7fdbd4748245 |
completed | March 9, 2026, 1:49 a.m. |
Created at: March 4, 2026, 7:43 p.m.