Triple
T16184085
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schöneberg municipal railway |
E392753
|
entity |
| Predicate | lineLengthOperated_km |
P69216
|
FINISHED |
| Object | approximately 2.9 |
—
|
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: approximately 2.9 | Statement: [Schöneberg municipal railway, lineLengthOperated_km, approximately 2.9]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lineLengthOperated_km Context triple: [Schöneberg municipal railway, lineLengthOperated_km, approximately 2.9]
-
A.
lengthInKm
Indicates that one entity specifies the length or distance of another entity measured in kilometers.
-
B.
mainStraightLengthKm
Indicates the length, measured in kilometers, of the primary straight segment associated with the entity.
-
C.
trackLengthApproxKm
chosen
Indicates that one entity has an approximate track length, measured in kilometers, associated with it.
-
D.
hasMainStraightLengthKm
Indicates the length in kilometers of the primary or main straight segment associated with an entity.
-
E.
railwayLineLength
Indicates the total measured length of a railway line.
- 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_69d87f1e49ac8190a311b54d32990576 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e2205fc080819097858f36253fef7c |
completed | April 17, 2026, 11:58 a.m. |
| PD | Predicate disambiguation | batch_69e219d642708190ba31a90dce76a210 |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:02 a.m.