Triple
T30817625
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belgian transport infrastructure |
E784826
|
entity |
| Predicate | roadNetworkLengthKm |
P14774
|
FINISHED |
| Object | approximately 154000 |
—
|
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 154000 | Statement: [Belgian transport infrastructure, roadNetworkLengthKm, approximately 154000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roadNetworkLengthKm Context triple: [Belgian transport infrastructure, roadNetworkLengthKm, approximately 154000]
-
A.
roadSystemLength
chosen
Indicates the total length or extent of a road network associated with an entity.
-
B.
trailSystemLength
Indicates the total measured length of a trail system associated with an entity.
-
C.
roadLength
Indicates the measured distance or extent of a road, typically expressed in units of length.
-
D.
mainStraightLengthKm
Indicates the length, measured in kilometers, of the primary straight segment associated with the entity.
-
E.
roadNetworkDensity
Indicates the concentration of roads within a given area, reflecting how densely the transportation network is developed.
- 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_69f224b4eda48190bd212ce4f3901e56 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6906994e88190a2da183455bdf076 |
completed | May 3, 2026, 12:01 a.m. |
| PD | Predicate disambiguation | batch_69f68b7d2794819092fef8a63f4f3de8 |
completed | May 2, 2026, 11:40 p.m. |
Created at: April 29, 2026, 8:44 p.m.