Triple
T206448
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moon |
E4619
|
entity |
| Predicate | surfaceFeatures |
P5378
|
FINISHED |
| Object | lunar maria |
—
|
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: lunar maria | Statement: [Moon, surfaceFeatures, lunar maria]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: surfaceFeatures Context triple: [Moon, surfaceFeatures, lunar maria]
-
A.
surfaceType
Indicates the kind or classification of surface associated with an entity or interaction.
-
B.
terrainFeature
chosen
Indicates a relationship where one entity is a natural or constructed landform or surface characteristic associated with a given location or area.
-
C.
featuresText
Indicates that an entity includes or presents a specific piece of text as one of its characteristics or contents.
-
D.
featureType
Indicates the specific kind or category of feature that characterizes or distinguishes an entity.
-
E.
skeletonFeature
Indicates that one entity is a structural or anatomical skeletal feature or component of another entity.
- 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_69a25737567c81908f9c505300239181 |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25e2aba74819093eddd8d820260c0 |
completed | Feb. 28, 2026, 3:16 a.m. |
| PD | Predicate disambiguation | batch_69a25b4c7f908190876c1041db52dffc |
completed | Feb. 28, 2026, 3:04 a.m. |
Created at: Feb. 28, 2026, 2:51 a.m.