Triple
T421669
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Albany–Rensselaer rail bridge |
E8115
|
entity |
| Predicate | locatedInWaterBodyRegion |
P1714
|
FINISHED |
| Object | upper Hudson 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: upper Hudson River | Statement: [Albany–Rensselaer rail bridge, locatedInWaterBodyRegion, upper Hudson River]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInWaterBodyRegion Context triple: [Albany–Rensselaer rail bridge, locatedInWaterBodyRegion, upper Hudson River]
-
A.
locatedInBodyOfWater
chosen
Indicates that an entity is situated within or on the surface of a specific body of water.
-
B.
locatedOnWaterbody
Indicates that an entity is situated on or directly adjacent to a specified body of water.
-
C.
appliesToWaterBody
Indicates that something (such as a rule, condition, property, or effect) is relevant or applicable specifically to a particular water body.
-
D.
bodyOfWater
Indicates that one entity is a body of water that is geographically or physically associated with another entity.
-
E.
connectsBodyOfWater
Indicates a relationship where one entity serves as a link or passage between two bodies of water, allowing them to be joined or interact.
- 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_69a2e7f1d1bc81909cf2dc9754a3c334 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2eec0e9dc81908c08b209ce5278ef |
completed | Feb. 28, 2026, 1:33 p.m. |
| PD | Predicate disambiguation | batch_69a2edd3b948819097d96c73d0a0f699 |
completed | Feb. 28, 2026, 1:29 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.