Triple
T7921623
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jacobi matrix |
E183956
|
entity |
| Predicate | hasSpectrum |
P48586
|
FINISHED |
| Object | real when symmetric and real |
—
|
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: real when symmetric and real | Statement: [Jacobi matrix, hasSpectrum, real when symmetric and real]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpectrum Context triple: [Jacobi matrix, hasSpectrum, real when symmetric and real]
-
A.
hasSpectralChannel
Indicates that something possesses or is associated with a specific spectral channel or band within an electromagnetic spectrum.
-
B.
hasSpectrograph
Indicates that one entity is equipped with or contains a spectrograph instrument.
-
C.
spectrumContains
Indicates that a given spectrum includes or exhibits a specified component, feature, or range within it.
-
D.
spectralProperty
chosen
Indicates a relationship where an entity possesses or is characterized by a specific spectral feature, measurement, or behavior (e.g., in its frequency, wavelength, or energy spectrum).
-
E.
usesHarmonics
Indicates that one entity employs harmonic frequencies or overtones of another entity or signal as part of its operation or behavior.
- 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_69ca828efbe48190bd48482650182e79 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3a9499cc8190b6bd81f4625c77ab |
completed | March 31, 2026, 3:08 a.m. |
| PD | Predicate disambiguation | batch_69cae9316e98819080be7bf1a6ff92f1 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 5:06 p.m.