Triple
T6204813
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parker Solar Probe |
E138720
|
entity |
| Predicate | heatShieldThickness |
P68903
|
FINISHED |
| Object | about 11.4 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 11.4 centimeters | Statement: [Parker Solar Probe, heatShieldThickness, about 11.4 centimeters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: heatShieldThickness Context triple: [Parker Solar Probe, heatShieldThickness, about 11.4 centimeters]
-
A.
heatShieldType
Indicates the specific kind or category of heat shield associated with an object or system.
-
B.
sideArmorThickness
Indicates the thickness of an object's armor specifically along its sides.
-
C.
deckArmorThickness
Indicates the thickness of the armor plating on the horizontal deck surface of a vehicle, vessel, or structure.
-
D.
armorThicknessMax
Indicates the maximum thickness of armor that an entity possesses or can withstand.
-
E.
armourThickness
Indicates the measured thickness of an entity’s protective armor in the context of defense or shielding.
- 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_69c008acbea48190991c6b834bb45d65 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0626d96ec8190816c00c44668177d |
completed | March 22, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_69c055fdea3c81908f5d910f0d36234a |
completed | March 22, 2026, 8:50 p.m. |
| PDg | Predicate description generation | batch_69c056c965ac8190b938502fa8c74e1b |
completed | March 22, 2026, 8:53 p.m. |
Created at: March 22, 2026, 4:20 p.m.