Triple
T1632262
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Norristown High Speed Line |
E35281
|
entity |
| Predicate | usesRightOfWayType |
P13660
|
FINISHED |
| Object | dedicated right-of-way |
—
|
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: dedicated right-of-way | Statement: [Norristown High Speed Line, usesRightOfWayType, dedicated right-of-way]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesRightOfWayType Context triple: [Norristown High Speed Line, usesRightOfWayType, dedicated right-of-way]
-
A.
someRightOfWayUsedBy
chosen
Indicates that a particular right of way is utilized or traversed by a specified user, route, or transport entity.
-
B.
ownerOfRightOfWay
Indicates that one entity holds the legal right to pass through or use a specific path, route, or area on another entity’s property.
-
C.
hasPedestrianPriority
Indicates that pedestrians are given precedence or right-of-way over other road users in a particular context or area.
-
D.
hasApproachRoad
Indicates that one entity is connected to or accessed by another entity via an approach road leading to it.
-
E.
roadSide
Indicates that one entity is located along, beside, or immediately adjacent to a road.
- 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_69a886036bc081909ff5de16dbe5e8ea |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a9431af5ac8190893133f1ae490142 |
completed | March 5, 2026, 8:47 a.m. |
| PD | Predicate disambiguation | batch_69a907c91c888190b6ed295c1a2e0977 |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:28 p.m.