Triple
T4618278
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rupes (scarps) on Mercury |
E100919
|
entity |
| Predicate | hasTypicalHeight |
P573
|
FINISHED |
| Object | hundreds of meters |
—
|
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: hundreds of meters | Statement: [Rupes (scarps) on Mercury, hasTypicalHeight, hundreds of meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalHeight Context triple: [Rupes (scarps) on Mercury, hasTypicalHeight, hundreds of meters]
-
A.
typicalHeight
chosen
Indicates the usual or characteristic height associated with an entity, such as a person, object, or species.
-
B.
hasHeight
Indicates that one entity possesses a specific vertical measurement or stature.
-
C.
averageHeight
Indicates that the relationship specifies the mean height value calculated from a set of entities or measurements.
-
D.
heightInInches
Indicates that one entity has a specific height measured in inches.
-
E.
heightInCentimetres
Indicates the numerical value of an entity’s height measured in centimetres.
- 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.