Triple
T2580877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Forest Park (Portland, Oregon) |
E57086
|
entity |
| Predicate | hasTrailSystemLength |
P14630
|
FINISHED |
| Object | over 80 miles of trails |
—
|
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: over 80 miles of trails | Statement: [Forest Park (Portland, Oregon), hasTrailSystemLength, over 80 miles of trails]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTrailSystemLength Context triple: [Forest Park (Portland, Oregon), hasTrailSystemLength, over 80 miles of trails]
-
A.
hasTrailLength
Indicates that an entity (such as a trail or route) has a specific measured length.
-
B.
trailSystemLength
chosen
Indicates the total measured length of a trail system associated with an entity.
-
C.
hasTrail
Indicates that an entity possesses, includes, or is associated with a trail or pathway.
-
D.
hasTrailType
Indicates that an entity (such as a trail or route) is associated with a specific type or category of trail.
-
E.
trailLengthApprox
Indicates an approximate measurement of the total length of a trail.
- 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_69ab4a4dca6481908c301f8e317396e7 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd3c6da888190ba7abfe37d182602 |
completed | March 7, 2026, 7:29 a.m. |
| PD | Predicate disambiguation | batch_69abd0cfeae08190aed03866ba071c5c |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:49 p.m.