Triple
T26735933
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nobeyama Radio Observatory |
E674108
|
entity |
| Predicate | arrayType |
P161182
|
FINISHED |
| Object | radio interferometer |
—
|
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: radio interferometer | Statement: [Nobeyama Radio Observatory, arrayType, radio interferometer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: arrayType Context triple: [Nobeyama Radio Observatory, arrayType, radio interferometer]
-
A.
ariaType
Indicates that one entity is classified as a specific type or category within the ARIA (Accessible Rich Internet Applications) specification.
-
B.
arrangementType
Indicates the specific kind or category of arrangement that characterizes how the related entities are organized or structured in relation to each other.
-
C.
allyType
Indicates that one entity is classified as a specific type or category of ally in relation to another entity.
-
D.
vectorType
Indicates that one entity is classified as the type or category of vector associated with another entity.
-
E.
argumentType
Indicates that one entity serves as a specific semantic or syntactic argument role (such as subject, object, or complement) in relation to another entity or event.
- 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_69eecda57ab481909424e98f2835e7d8 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f61844d7f8819081080f687999b77a |
completed | May 2, 2026, 3:29 p.m. |
| PD | Predicate disambiguation | batch_69f60b8dfa0c8190864e1a940024d0a0 |
completed | May 2, 2026, 2:34 p.m. |
| PDg | Predicate description generation | batch_69f6106d346c8190868489f36c65b6ec |
completed | May 2, 2026, 2:55 p.m. |
Created at: April 27, 2026, 3:47 a.m.