Triple
T32793873
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U.S. Route 302 in Maine |
E838704
|
entity |
| Predicate | hasApproximateLengthInState |
P192661
|
FINISHED |
| Object | about 100 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: about 100 miles | Statement: [U.S. Route 302 in Maine, hasApproximateLengthInState, about 100 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateLengthInState Context triple: [U.S. Route 302 in Maine, hasApproximateLengthInState, about 100 miles]
-
A.
hasApproximateLengthCategory
Indicates that one entity is classified into a broad or approximate category based on its length.
-
B.
hasMaxLengthApprox
Indicates that something has a maximum length that is approximately equal to a specified value, allowing for some tolerance or imprecision.
-
C.
hasApproximateEnd
Indicates that an entity’s end point, time, or boundary is known only approximately rather than precisely.
-
D.
hasApproximateDuration
Indicates that one entity has a duration that is estimated or not exact, typically expressed as an approximate length of time.
-
E.
hasApproximateNumberOfSymbols
Indicates that an entity is associated with a quantity of symbols that is approximate rather than exact.
- F. None of above. chosen
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_69f3493c7f6881908edf2aa13631d1e0 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fd231cab588190ad0953dc8f4af8f2 |
completed | May 7, 2026, 11:41 p.m. |
| PD | Predicate disambiguation | batch_69fd1aa3f1c481909fe6e9cab1383551 |
completed | May 7, 2026, 11:05 p.m. |
| PDg | Predicate description generation | batch_69fd231bdd108190900369e07c854e95 |
completed | May 7, 2026, 11:41 p.m. |
Created at: May 1, 2026, 1:14 a.m.