Triple
T20788278
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rasender Roland |
E511698
|
entity |
| Predicate | approximateLineLength |
P39661
|
FINISHED |
| Object | about 24 km |
—
|
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: about 24 km | Statement: [Rasender Roland, approximateLineLength, about 24 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateLineLength Context triple: [Rasender Roland, approximateLineLength, about 24 km]
-
A.
lineLengthType
Indicates the type or category used to characterize the length of a line.
-
B.
hasLineLength
chosen
Indicates that one entity has, is characterized by, or is associated with a specific line length value.
-
C.
approximateLengthInMeters
Indicates the estimated or roughly measured length of something expressed in meters.
-
D.
hasApproximateLineCount
Indicates that one entity is associated with an estimated or non-exact number of lines represented by the other entity.
-
E.
approximateBlockLength
Indicates that one entity specifies or estimates the length of a block in an approximate or non-exact manner.
- 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_69e0b4cb83948190bd57bec21d78ed53 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c28dfb8c8190a10289c157a61c67 |
completed | April 21, 2026, 12:19 a.m. |
| PD | Predicate disambiguation | batch_69e5c0575b1c81908d010223fcd1213e |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 12:38 p.m.