Triple
T7658259
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Epsilon Eridani b |
E173438
|
entity |
| Predicate | radialVelocitySignalAmplitude |
P76149
|
FINISHED |
| Object | tens of m/s |
—
|
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: tens of m/s | Statement: [Epsilon Eridani b, radialVelocitySignalAmplitude, tens of m/s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: radialVelocitySignalAmplitude Context triple: [Epsilon Eridani b, radialVelocitySignalAmplitude, tens of m/s]
-
A.
radialVelocityAmplitude
chosen
Indicates the magnitude of variation in an object's radial (line-of-sight) velocity, typically representing the semi-amplitude of its periodic Doppler shift.
-
B.
hasRadialVelocity_km_per_s
Indicates that one entity has a measured radial velocity, expressed in kilometers per second, relative to another reference frame or object.
-
C.
hasRadialVelocitySignature
Indicates that an object exhibits a measurable radial velocity pattern characteristic of a specific physical process or source.
-
D.
lightcurveAmplitude
Indicates the measured range of brightness variation of an object over time in its light curve.
-
E.
hasRadialVelocityDispersion
Indicates that an entity exhibits a spread in its radial velocities, quantifying how much the line-of-sight speeds of its components differ from one another.
- 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_69c69955517c819085bc715b96d304d2 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7061cbc3c8190a917dd7e71214182 |
completed | March 27, 2026, 10:35 p.m. |
| PD | Predicate disambiguation | batch_69c7015dd8fc8190bc5f52a12bd46209 |
completed | March 27, 2026, 10:14 p.m. |
Created at: March 27, 2026, 3:59 p.m.