Triple
T25941918
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York State Route 38 |
E653725
|
entity |
| Predicate | traversesAreaBetween |
P34612
|
FINISHED |
| Object | Finger Lakes region |
E11901
|
NE 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: Finger Lakes region | Statement: [New York State Route 38, traversesAreaBetween, Finger Lakes region]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: traversesAreaBetween Context triple: [New York State Route 38, traversesAreaBetween, Finger Lakes region]
-
A.
regionTraversedBy
Indicates that a region is crossed or passed through by a specified path, route, or linear feature.
-
B.
passesThroughArea
chosen
Indicates that an entity moves or extends through the spatial region defined by another entity or area.
-
C.
locatedBetween
Indicates that one entity is positioned spatially between two other reference entities.
-
D.
exploresBoundaryBetween
Indicates a relationship in which one entity actively investigates, tests, or probes the limits or dividing line between two domains, states, or concepts.
-
E.
includesRouteBetween
Indicates that one entity (such as a service, plan, or network) contains or provides a specific route connecting two locations or points.
- F. None of above.
Provenance (4 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_69e7ab3fd2f881908837305e4ba98011 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f61f12b0f08190bc4a16907941864c |
completed | May 2, 2026, 3:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a1107745e248190890a67b6627831a4 |
completed | May 23, 2026, 1:48 a.m. |
| PD | Predicate disambiguation | batch_69f61b37a5648190b10d33ae205ccfee |
completed | May 2, 2026, 3:41 p.m. |
Created at: April 22, 2026, 8:40 a.m.