Triple
T14174985
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Town of Ulysses, New York |
E351307
|
entity |
| Predicate | hasLakeShoreRecreation |
P103251
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Town of Ulysses, New York, hasLakeShoreRecreation, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLakeShoreRecreation Context triple: [Town of Ulysses, New York, hasLakeShoreRecreation, yes]
-
A.
hasLakeshore
Indicates that one entity is located along or directly borders the shore of a lake associated with another entity.
-
B.
hasCoastalRecreation
chosen
Indicates that an entity provides, supports, or is associated with recreational activities occurring along a coast or shoreline.
-
C.
hasShorelineTrail
Indicates that a location or body of water is connected to or bordered by a trail that runs along its shoreline.
-
D.
hasRecreationalArea
Indicates that an entity includes, provides, or is associated with a designated space intended for leisure or recreational activities.
-
E.
hasWaterfrontPark
Indicates that a place or area includes or is associated with a park located directly along a body of water.
- 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_69d8278834a08190b0f1784e58d7b99c |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61b7cc3081909f4fa371e1eae130 |
completed | April 14, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69de05baed64819096590e5618a3a8ed |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 10, 2026, 1:02 a.m.