Triple
T18255833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haskell committee |
E437220
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Haskell 98 |
—
|
NE NERFINISHED |
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: Haskell 98 | Statement: [Haskell committee, notableWork, Haskell 98]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Haskell 98 Context triple: [Haskell committee, notableWork, Haskell 98]
-
A.
Haskell
chosen
Haskell is a statically typed, purely functional programming language known for its strong type system, lazy evaluation, and use in both academic research and industry.
-
B.
Haskell
Haskell is a small town in Muskogee County, Oklahoma, known for its rural character and local community life.
-
C.
Haskell committee
The Haskell committee is the group of researchers and language designers responsible for specifying and standardizing the Haskell functional programming language.
-
D.
Standard ML of New Jersey
Standard ML of New Jersey is a well-known, optimizing compiler and interactive environment for the Standard ML programming language, widely used in research and teaching.
-
E.
GHC
GHC (Glasgow Haskell Compiler) is the most widely used, feature-rich, and optimizing compiler for the Haskell programming language.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b913351c8190932b6a426de04b41 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4fd85ee548190a102611fcf709ad4 |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 10:34 a.m.