Triple
T19027272
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mariners’ Museum and Park |
E465640
|
entity |
| Predicate | NolandTrailLength |
P18078
|
FINISHED |
| Object | approximately 5 miles |
—
|
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: approximately 5 miles | Statement: [Mariners’ Museum and Park, NolandTrailLength, approximately 5 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: NolandTrailLength Context triple: [Mariners’ Museum and Park, NolandTrailLength, approximately 5 miles]
-
A.
longDistanceTrail
Indicates that a trail or route spans a considerable distance, typically intended for extended or multi-day travel.
-
B.
trailLengthApprox
chosen
Indicates an approximate measurement of the total length of a trail.
-
C.
longDistanceTrailEnd
Indicates that a location serves as the endpoint or terminus of a long-distance trail.
-
D.
trailLengthCategory
Indicates the classification of a trail based on its total length (e.g., short, medium, long).
-
E.
trailName
Indicates the name assigned to a specific trail or path in the relationship.
- 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_69d8dd0359648190bc2a9202c5cf29d2 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d73dc404819092059e496662d151 |
completed | April 20, 2026, 7:35 a.m. |
| PD | Predicate disambiguation | batch_69e4a2fd80c081908237317a3a883e1c |
completed | April 19, 2026, 9:40 a.m. |
Created at: April 10, 2026, 12:02 p.m.