Triple
T1691878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sangli |
E36566
|
entity |
| Predicate | roadConnectivity |
P3374
|
FINISHED |
| Object | connected by national and state highways |
—
|
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: connected by national and state highways | Statement: [Sangli, roadConnectivity, connected by national and state highways]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roadConnectivity Context triple: [Sangli, roadConnectivity, connected by national and state highways]
-
A.
roadSystem
Indicates a relationship where multiple roads are organized and connected as part of a larger, integrated transportation network or infrastructure.
-
B.
streetNetwork
chosen
Indicates the layout and connectivity relationships among streets within a geographic area, including how roads intersect, link, and form a navigable network.
-
C.
transportNetwork
Indicates a relationship where infrastructure or services enable the movement of people or goods between different locations.
-
D.
ropewayConnects
Indicates that a ropeway (such as a cable car or gondola system) provides a direct transportation connection between two locations.
-
E.
linkedByRoadTo
Indicates that two locations are directly connected to each other by a road suitable for travel.
- 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_69a886151508819084fa7f1ce6e05577 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aaf3359ce48190803b322db8ad6027 |
completed | March 6, 2026, 3:31 p.m. |
| PD | Predicate disambiguation | batch_69aa61b71cec8190b273588051058ebd |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:29 p.m.