Triple
T6130556
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Storrow Drive |
E136705
|
entity |
| Predicate | hasAtGradeIntersections |
P3381
|
FINISHED |
| Object | limited |
—
|
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: limited | Statement: [Storrow Drive, hasAtGradeIntersections, limited]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAtGradeIntersections Context triple: [Storrow Drive, hasAtGradeIntersections, limited]
-
A.
hasGradeCrossings
Indicates that there are one or more level crossings where a road, path, or similar route intersects the railway or track at the same grade.
-
B.
hasAtGradeCrossingNearby
chosen
Indicates that one entity (typically a location or segment) has a nearby at-grade crossing where two transportation paths intersect at the same level.
-
C.
hasNotableIntersection
Indicates that two entities intersect or cross at a point that is considered significant or noteworthy in some context.
-
D.
hasGradeSeparatedInterchanges
Indicates that the route or roadway includes interchanges where traffic flows are separated by different levels (e.g., overpasses/underpasses) rather than intersecting at the same grade.
-
E.
hadCrossingPoints
Indicates that two entities intersected or overlapped at one or more specific points in space or time.
- 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_69c008a0a37c81908e5b4f879158afb3 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05c4de9c48190b98f67a6251ec1df |
completed | March 22, 2026, 9:17 p.m. |
| PD | Predicate disambiguation | batch_69c055f19b0c81908be34a00ab218723 |
completed | March 22, 2026, 8:49 p.m. |
Created at: March 22, 2026, 4:15 p.m.