Triple
T747198
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | China Brook |
E15368
|
entity |
| Predicate | hasFlowDirection |
P8846
|
FINISHED |
| Object | generally downstream toward the Croton River |
—
|
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: generally downstream toward the Croton River | Statement: [China Brook, hasFlowDirection, generally downstream toward the Croton River]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFlowDirection Context triple: [China Brook, hasFlowDirection, generally downstream toward the Croton River]
-
A.
dataFlowDirection
Indicates the direction in which data moves or is transmitted from a source entity to a target entity.
-
B.
hasTrafficDirection
Indicates that there is a specified flow or orientation of traffic associated with an entity (such as a road, lane, or route).
-
C.
hasFlowRegime
Indicates that one entity is characterized by, or operates under, a particular pattern or regime of flow.
-
D.
hasRouteDirection
Indicates that a specified route is associated with a particular travel direction (e.g., inbound, outbound, northbound).
-
E.
drainageDirection
chosen
Indicates the direction in which water or other fluids flow or are drained away from a given point or 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_69a49358aa308190adbc9b5a0a2adcf9 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a62dd1bc819094a3814654448ae3 |
completed | March 1, 2026, 8:48 p.m. |
| PD | Predicate disambiguation | batch_69a4a4ff10608190bfd60b4a1cb38f7d |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.