Triple
T31646358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SML/NJ |
E807593
|
entity |
| Predicate | hasPrimaryImplementationLanguage |
P46793
|
FINISHED |
| Object | Standard ML |
—
|
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: Standard ML | Statement: [SML/NJ, hasPrimaryImplementationLanguage, Standard ML]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimaryImplementationLanguage Context triple: [SML/NJ, hasPrimaryImplementationLanguage, Standard ML]
-
A.
hasSecondaryImplementationLanguage
Indicates that an entity (such as a software system or component) uses a particular programming language as a secondary or auxiliary implementation language in addition to its primary one.
-
B.
languageOfPrimaryCompilation
Indicates the programming or source language in which an entity was primarily compiled.
-
C.
languageOfImplementation
Indicates the programming language in which a given software system, component, or algorithm is implemented.
-
D.
implementedInLanguage
chosen
Indicates that a piece of software or code is written using a particular programming language.
-
E.
hasPrimaryLanguageOfOperations
Indicates that an entity conducts its main activities or operations primarily using a specified language.
- F. None of above.
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_69f348d9ce58819093ea2da83cbeeec1 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_6a007899cadc8190a04edd503eaf6514 |
completed | May 10, 2026, 12:22 p.m. |
| PD | Predicate disambiguation | batch_6a0078493e088190b0c5047cbe75d304 |
completed | May 10, 2026, 12:21 p.m. |
Created at: April 30, 2026, 10:51 p.m.