Triple
T4618279
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rupes (scarps) on Mercury |
E100919
|
entity |
| Predicate | hasMaximumHeight |
P9788
|
FINISHED |
| Object | up to about 3 kilometers |
—
|
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: up to about 3 kilometers | Statement: [Rupes (scarps) on Mercury, hasMaximumHeight, up to about 3 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMaximumHeight Context triple: [Rupes (scarps) on Mercury, hasMaximumHeight, up to about 3 kilometers]
-
A.
hasHeight
chosen
Indicates that one entity possesses a specific vertical measurement or stature.
-
B.
hasApproximateMaximumWidth
Indicates that an entity’s maximum width is known only approximately, rather than as an exact value.
-
C.
heightRestriction
Indicates that there is a limit or constraint on how tall an entity is allowed or required to be in a given context.
-
D.
hasMaximumThickness
Indicates that an entity possesses a specified upper limit on its thickness.
-
E.
hasMaximumValue
Indicates that one value in a set is the greatest or highest possible according to a specified criterion.
- 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_69bd43cf363c819087fd5ab441b4a3f4 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd59e247448190ad92f194cb1127c5 |
completed | March 20, 2026, 2:29 p.m. |
| PD | Predicate disambiguation | batch_69bd522fd5c48190ad2bffc0a5bc9061 |
completed | March 20, 2026, 1:57 p.m. |
Created at: March 20, 2026, 1:12 p.m.