Triple
T156196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sun |
E3186
|
entity |
| Predicate | fractionHydrogenByMass |
P7288
|
FINISHED |
| Object | about 73 percent |
—
|
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 73 percent | Statement: [Sun, fractionHydrogenByMass, about 73 percent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fractionHydrogenByMass Context triple: [Sun, fractionHydrogenByMass, about 73 percent]
-
A.
hasMeanDensity
Indicates that one entity possesses a specified average mass per unit volume (mean density).
-
B.
hasMainAtmosphericComponent
Indicates that one entity has another entity as the primary constituent of its atmosphere.
-
C.
hasHigherSalinityThan
Indicates that one entity has a greater concentration of dissolved salts than another entity.
-
D.
fueledBy
Indicates that one entity provides the energy or power source that enables the operation or functioning of another entity.
-
E.
subunitRatio
Indicates the proportional relationship between the quantities or sizes of different subunits within a larger whole.
- F. None of above. chosen
Provenance (4 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_69a2527757ec819090b8becb2cf1a862 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a258808ff08190a06b6206f635612b |
completed | Feb. 28, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69a2565ded588190a27319aaa0130b4f |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a2587e598c81909e1082b813971f48 |
completed | Feb. 28, 2026, 2:52 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.