Triple
T3931042
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northside Trail |
E90793
|
entity |
| Predicate | trailNetworkType |
P51754
|
FINISHED |
| Object | urban trail network |
—
|
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: urban trail network | Statement: [Northside Trail, trailNetworkType, urban trail network]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trailNetworkType Context triple: [Northside Trail, trailNetworkType, urban trail network]
-
A.
routeNetworkType
Indicates the specific kind of transportation or communication network to which a route belongs (e.g., road, rail, or air).
-
B.
transportNetwork
Indicates a relationship where infrastructure or services enable the movement of people or goods between different locations.
-
C.
networkType
Indicates the category or kind of network associated with or used by an entity (e.g., wired, wireless, virtual, or specific protocol-based networks).
-
D.
beltwayType
Indicates the specific classification or type of a beltway (ring road) associated with a given roadway or area.
-
E.
streetNetwork
Indicates the layout and connectivity relationships among streets within a geographic area, including how roads intersect, link, and form a navigable network.
- F. None of above. chosen
Provenance (4 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_69aed95f26e0819094b0e71974543a19 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeeda98058819094dd6ab223670860 |
completed | March 9, 2026, 3:56 p.m. |
| PD | Predicate disambiguation | batch_69aee7609c4081908000ce12ae827c3f |
completed | March 9, 2026, 3:29 p.m. |
| PDg | Predicate description generation | batch_69aeeb5f859c819095b61f5ba8eace4f |
completed | March 9, 2026, 3:46 p.m. |
Created at: March 9, 2026, 3:23 p.m.