Triple
T26803738
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Freccia Alata Plus |
E671167
|
entity |
| Predicate | programNameLanguage |
P164296
|
FINISHED |
| Object | Italian |
—
|
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: Italian | Statement: [Freccia Alata Plus, programNameLanguage, Italian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: programNameLanguage Context triple: [Freccia Alata Plus, programNameLanguage, Italian]
-
A.
programLanguage
Indicates that an entity is implemented, written, or expressed using a particular programming language.
-
B.
primaryLanguageOfPrograms
Indicates that a given language is the main programming language used to implement or develop the specified programs.
-
C.
languageName
Indicates the specific name assigned to a language in the relationship.
-
D.
languageOfProgramming
Indicates that one entity is a programming language used to implement, develop, or script the other entity.
-
E.
programmingLanguage
Indicates that one entity is a programming language used to create, control, or interact with the other entity.
- 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_69eeb31fbd888190a82dac5822e453bc |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f644de4a84819087ddb84757fc4585 |
completed | May 2, 2026, 6:39 p.m. |
| PD | Predicate disambiguation | batch_69f641dc8ff48190ab575d855616580c |
completed | May 2, 2026, 6:26 p.m. |
| PDg | Predicate description generation | batch_69f643e818d481908fc66bc91bd25d77 |
completed | May 2, 2026, 6:35 p.m. |
Created at: April 27, 2026, 4:25 a.m.