Triple
T15839680
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ginga |
E384068
|
entity |
| Predicate | mainInstrumentEffectiveArea |
P50295
|
FINISHED |
| Object | about 4000 square centimeters |
—
|
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: about 4000 square centimeters | Statement: [Ginga, mainInstrumentEffectiveArea, about 4000 square centimeters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainInstrumentEffectiveArea Context triple: [Ginga, mainInstrumentEffectiveArea, about 4000 square centimeters]
-
A.
effectiveArea
chosen
Indicates the portion of a surface or region that actually contributes to a specified effect, such as performance, interaction, or impact, within a given context.
-
B.
areaSquareDegrees
Indicates the extent of a region or object measured as an area on the sky in square degrees.
-
C.
hasFocalPlaneArea
Indicates that an entity has a specific area measurement associated with its focal plane.
-
D.
coreAreaOf
Indicates that one entity is the central, primary, or most important area or domain of focus for another entity.
-
E.
imagingInstrument
Indicates that a particular instrument or device is used to capture or produce an image of a target or subject.
- 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_69d86da34c888190976e06c4019d415a |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e142e69360819091ea0556bd66d785 |
completed | April 16, 2026, 8:13 p.m. |
| PD | Predicate disambiguation | batch_69e005418f588190824d91ff7974dada |
completed | April 15, 2026, 9:38 p.m. |
Created at: April 10, 2026, 4:49 a.m.