Triple
T20044258
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sharpless crater |
E497511
|
entity |
| Predicate | hasRegolithBehavior |
P138477
|
FINISHED |
| Object | loose material susceptible to mass wasting |
—
|
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: loose material susceptible to mass wasting | Statement: [Sharpless crater, hasRegolithBehavior, loose material susceptible to mass wasting]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRegolithBehavior Context triple: [Sharpless crater, hasRegolithBehavior, loose material susceptible to mass wasting]
-
A.
hasRegolith
Indicates that one entity possesses, contains, or is covered by regolith (a layer of loose, unconsolidated surface material).
-
B.
hasRegolithDepth
Indicates the depth or thickness of a layer of regolith present on a surface or object.
-
C.
surfaceRegolithDepth_m
Indicates the measured thickness of the loose surface regolith layer at a location, expressed in meters.
-
D.
hasRockType
Indicates that an entity is composed of, characterized by, or associated with a specific type of rock.
-
E.
hasHeavilyCrateredSurface
Indicates that the subject’s surface is densely covered with impact craters, showing extensive cratering relative to typical surfaces.
- 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_69da627278c88190babe4297a9df1236 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e662eea09481908d1001165e9d719c |
completed | April 20, 2026, 5:31 p.m. |
| PD | Predicate disambiguation | batch_69e54ce752748190a0a1ffddd0372271 |
completed | April 19, 2026, 9:45 p.m. |
| PDg | Predicate description generation | batch_69e54fc20888819083c9118a09d0d2dc |
completed | April 19, 2026, 9:57 p.m. |
Created at: April 11, 2026, 3:37 p.m.