Triple
T19260316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Navy Precision Optical Interferometer |
E481629
|
entity |
| Predicate | hasBaselineType |
P24990
|
FINISHED |
| Object | Y-shaped array |
—
|
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: Y-shaped array | Statement: [Navy Precision Optical Interferometer, hasBaselineType, Y-shaped array]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBaselineType Context triple: [Navy Precision Optical Interferometer, hasBaselineType, Y-shaped array]
-
A.
hasBaselineLength
Indicates that one entity has a specified baseline length measurement in relation to another entity or reference.
-
B.
usesBaseline
Indicates that one entity relies on or applies another entity as a reference baseline for comparison, measurement, or evaluation.
-
C.
baselineType
chosen
Indicates the type or category of a baseline used as a reference point for comparison or evaluation.
-
D.
hasFanBaseType
Indicates that an entity has a particular type or category of fan base associated with it.
-
E.
hasStandardType
Indicates that something conforms to or is categorized under a defined standard classification or type.
- 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_69d8e8cd9d1081908a181d02b88b59b8 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fb890e7c8190beba407f63459382 |
completed | April 20, 2026, 10:10 a.m. |
| PD | Predicate disambiguation | batch_69e4dd002d00819088b625056edfb74e |
completed | April 19, 2026, 1:47 p.m. |
Created at: April 10, 2026, 1:28 p.m.