Triple
T29089788
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fujitsu FM-7 |
E734822
|
entity |
| Predicate | bundledLanguage |
P2177
|
FINISHED |
| Object | F-BASIC interpreter |
—
|
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: F-BASIC interpreter | Statement: [Fujitsu FM-7, bundledLanguage, F-BASIC interpreter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bundledLanguage Context triple: [Fujitsu FM-7, bundledLanguage, F-BASIC interpreter]
-
A.
packagingLanguage
Indicates the language used on or in the product’s packaging.
-
B.
languageBranch
Indicates that one language belongs to, or is classified under, a broader linguistic branch or subgroup.
-
C.
includesLanguage
chosen
Indicates that one entity contains, supports, or makes use of a specified language as part of its content, functionality, or representation.
-
D.
hasLanguageOn
Indicates that an entity uses or is associated with a particular language in a specific context, medium, or location.
-
E.
coexistsWithLanguage
Indicates that one entity exists or functions alongside a particular language at the same time, without excluding or replacing it.
- 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_69f05b0ed66481908f2e864fa550d2f1 |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f6617c613c81908d5886952f4594ff |
completed | May 2, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69f65c2376a08190be5215171e908e69 |
completed | May 2, 2026, 8:18 p.m. |
Created at: April 28, 2026, 11:04 a.m.