Triple
T19831836
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | radio source W1 |
E476478
|
entity |
| Predicate | hasCompactness |
P56994
|
FINISHED |
| Object | compact |
—
|
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: compact | Statement: [radio source W1, hasCompactness, compact]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCompactness Context triple: [radio source W1, hasCompactness, compact]
-
A.
isCompact
chosen
Indicates that an object or space has a small, efficiently arranged size or volume relative to its function or contents.
-
B.
typeOfCompactness
Indicates the specific kind or category of compactness that characterizes an entity or structure.
-
C.
isNoncompact
Indicates that the object (such as a space or set) lacks compactness, meaning it does not satisfy the property that every open cover has a finite subcover.
-
D.
hasComplexity
Indicates that something possesses a certain level or type of complexity, often in terms of structure, behavior, or difficulty.
-
E.
compactedVariantUsedFor
Indicates that one entity is a compacted or compressed version of another entity that is used in its place for some purpose.
- 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_69d8e51c7c188190b926f3a2a7b5f881 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e656ce68b48190aa25b29d0b6ea021 |
completed | April 20, 2026, 4:39 p.m. |
| PD | Predicate disambiguation | batch_69e5305bda388190a23b7191768107b1 |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 1:50 p.m.