Triple
T20835676
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miljacka |
E512952
|
entity |
| Predicate | hasBridgeDensity |
P20771
|
FINISHED |
| Object | many bridges within a short urban stretch |
—
|
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: many bridges within a short urban stretch | Statement: [Miljacka, hasBridgeDensity, many bridges within a short urban stretch]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBridgeDensity Context triple: [Miljacka, hasBridgeDensity, many bridges within a short urban stretch]
-
A.
hasNumberOfBridges
chosen
Indicates the quantitative relationship specifying how many bridges are associated with a given entity.
-
B.
hasBridgeTo
Indicates that one entity is connected to another by a bridge or bridging structure that allows passage or linkage between them.
-
C.
hasBridgeCrossings
Indicates that one entity has one or more bridge structures that span across or connect over another entity (such as a road, river, or area).
-
D.
hasBridges
Indicates that one entity possesses, contains, or is characterized by one or more bridges connecting locations or components.
-
E.
hasMajorBridge
Indicates that one entity possesses or includes a primary or significant bridge associated with it.
- 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_69e0b4cf62a88190bbf92351e9e57259 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c32622c481908b8d2159bd5bb0ad |
completed | April 21, 2026, 12:21 a.m. |
| PD | Predicate disambiguation | batch_69e5c9a1f4f48190aa9fb4ef8f8aea5a |
completed | April 20, 2026, 6:37 a.m. |
Created at: April 16, 2026, 12:42 p.m.