Triple
T25330801
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | East–West corridor – Green Line |
E635144
|
entity |
| Predicate | riverCrossedByTunnel |
P67400
|
FINISHED |
| Object | Hooghly River |
—
|
NE NERFINISHED |
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: Hooghly River | Statement: [East–West corridor – Green Line, riverCrossedByTunnel, Hooghly River]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: riverCrossedByTunnel Context triple: [East–West corridor – Green Line, riverCrossedByTunnel, Hooghly River]
-
A.
crossedByTunnel
chosen
Indicates that one entity (typically a barrier like a mountain, river, or road) is traversed or passed through by another entity via a tunnel.
-
B.
crossedByRiver
Indicates that a river passes across or through a specified area, feature, or route.
-
C.
waterwayTypeCrossed
Indicates the specific kind of waterway (e.g., river, canal, stream) that is being crossed in the described relationship or action.
-
D.
hasRiverCrossingType
Indicates the type or nature of a river crossing associated with an entity (e.g., bridge, ford, ferry).
-
E.
hasCanalCrossing
Indicates that one entity is connected to or traversed by another via a canal crossing, such as a bridge, aqueduct, or similar structure over a canal.
- 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_69e75a9908108190a95427a97020632a |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f5ffc74fa481909b4fe24a9337f9eb |
completed | May 2, 2026, 1:44 p.m. |
| PD | Predicate disambiguation | batch_69f5f7f99dc08190afcfb3bc4dfbec1d |
completed | May 2, 2026, 1:11 p.m. |
Created at: April 21, 2026, 1:30 p.m.