Triple
T2734365
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suramadu Bridge |
E60592
|
entity |
| Predicate | urbanConnection |
P4245
|
FINISHED |
| Object | connects Surabaya with Bangkalan on Madura |
—
|
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: connects Surabaya with Bangkalan on Madura | Statement: [Suramadu Bridge, urbanConnection, connects Surabaya with Bangkalan on Madura]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: urbanConnection Context triple: [Suramadu Bridge, urbanConnection, connects Surabaya with Bangkalan on Madura]
-
A.
connectsCity
chosen
Indicates a relationship where one entity serves as a link or route that joins or provides direct access between two cities.
-
B.
urbanComponent
Indicates that something functions as a constituent part or element within an urban area or city system.
-
C.
linkedCity
Indicates that two entities are associated with each other through a specific city, such as being located in, connected via, or related by that city.
-
D.
cityWide
Indicates that something applies to, affects, or extends across an entire city.
-
E.
connectsDowntownTo
Indicates a relationship where one location, route, or service provides a direct connection or access to a downtown area.
- 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_69ab4b77febc819095603eb012cd141b |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdb0e7b888190bfa5d2e33f00ec0f |
completed | March 7, 2026, 8 a.m. |
| PD | Predicate disambiguation | batch_69abd82859348190bce3be8f2e9d60ba |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:56 p.m.