Triple
T37604116
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Papikondalu |
E935600
|
entity |
| Predicate | boatCruiseRoute |
P7985
|
FINISHED |
| Object | Rajahmundry to Papikondalu |
—
|
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: Rajahmundry to Papikondalu | Statement: [Papikondalu, boatCruiseRoute, Rajahmundry to Papikondalu]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: boatCruiseRoute Context triple: [Papikondalu, boatCruiseRoute, Rajahmundry to Papikondalu]
-
A.
sailingRoute
chosen
Indicates a path or course taken by a vessel when traveling by water from one location to another.
-
B.
marineRouteType
Indicates the specific kind or classification of a maritime route used for travel, transport, or navigation between locations.
-
C.
shipwreckRoute
Indicates a route or path along which a ship traveled or was intended to travel that ultimately resulted in a shipwreck at some point on that route.
-
D.
travelRouteOf
Indicates the path or itinerary that an entity follows or uses when traveling from one location to another.
-
E.
travelTimeByBoat
Indicates the amount of time it takes to travel between two locations specifically when using a boat as the mode of transportation.
- 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_69f76ed0a85481909254a8a89090c826 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbacaf54648190811ea33b34907e8e |
completed | May 6, 2026, 9:03 p.m. |
| PD | Predicate disambiguation | batch_69fba883f770819091059c6f6c6af9f7 |
completed | May 6, 2026, 8:45 p.m. |
Created at: May 3, 2026, 4:18 p.m.