Triple
T37485610
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hall-effect thrusters |
E931521
|
entity |
| Predicate | hasTypicalEfficiency |
P201271
|
FINISHED |
| Object | 40–70 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: 40–70 percent | Statement: [Hall-effect thrusters, hasTypicalEfficiency, 40–70 percent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalEfficiency Context triple: [Hall-effect thrusters, hasTypicalEfficiency, 40–70 percent]
-
A.
typicalEfficiencyComparedToPredecessor
Indicates how the usual or average efficiency of something compares to that of its predecessor.
-
B.
hasMaximumEfficiencyAt
Indicates that an entity reaches or exhibits its highest possible efficiency under a specified condition, context, or parameter value.
-
C.
claimedEfficiency
Indicates that an entity asserts or reports a certain level of efficiency, regardless of whether that efficiency is verified or actual.
-
D.
hasEfficiencyMetric
Indicates that an entity is associated with a specific measure or metric used to evaluate its efficiency.
-
E.
hasEfficiencySymbol
Indicates that an entity is associated with, or represented by, a specific symbol denoting its efficiency.
- 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_69f76ec382248190b47844df596123c6 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69ffe23081408190a121d901dbce1403 |
completed | May 10, 2026, 1:41 a.m. |
| PD | Predicate disambiguation | batch_69ffe18aed348190912a5996b2da728b |
completed | May 10, 2026, 1:38 a.m. |
| PDg | Predicate description generation | batch_69ffe22f453c81909867ee2d2047636f |
completed | May 10, 2026, 1:41 a.m. |
Created at: May 3, 2026, 4:17 p.m.