Triple
T13349725
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FLOW-MATIC |
E318038
|
entity |
| Predicate | languageLevel |
P109127
|
FINISHED |
| Object | third-generation programming language |
—
|
LITERAL 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: third-generation programming language | Statement: [FLOW-MATIC, languageLevel, third-generation programming language]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageLevel Context triple: [FLOW-MATIC, languageLevel, third-generation programming language]
-
A.
trainingLevel
Indicates the degree or stage of training or skill development that an entity has attained.
-
B.
languageOfCode
Indicates that a programming code artifact is written in, or uses, a particular programming language.
-
C.
languageProvision
Indicates that one entity supplies, supports, or makes available a particular language (or set of languages) for use by another entity.
-
D.
languageOfInterpretation
Indicates the language in which something (such as text, speech, or content) is interpreted or understood.
-
E.
officialLanguageVersion
Indicates that one language variant is the officially recognized form or version used for formal or administrative purposes in relation to another language or context.
- F. None of above. chosen
Provenance (4 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_69d806b5a3c08190b42c267fb092f98a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99e8b28e48190a23194e03a74b41b |
completed | April 11, 2026, 1:06 a.m. |
| PD | Predicate disambiguation | batch_69d98f6e53d88190bd6aa42f69b10ffb |
completed | April 11, 2026, 12:01 a.m. |
| PDg | Predicate description generation | batch_69d99073e4708190843bda3a1ae78f43 |
completed | April 11, 2026, 12:06 a.m. |
Created at: April 9, 2026, 9:31 p.m.