Triple
T147028
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Route 2 (Massachusetts) |
E3351
|
entity |
| Predicate | hasExpresswaySection |
P7229
|
FINISHED |
| Object | Boston to Lexington |
—
|
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: Boston to Lexington | Statement: [Route 2 (Massachusetts), hasExpresswaySection, Boston to Lexington]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasExpresswaySection Context triple: [Route 2 (Massachusetts), hasExpresswaySection, Boston to Lexington]
-
A.
hasMajorHighway
Indicates that a location or area is served by or directly connected to a major highway route.
-
B.
hasTollSegment
Indicates that a route, road, or path includes a segment where a toll must be paid.
-
C.
hasLanes
Indicates that an entity, such as a road or pathway, is divided into one or more distinct lanes for traffic or movement.
-
D.
hasApproachRoad
Indicates that one entity is connected to or accessed by another entity via an approach road leading to it.
-
E.
hasShuttleLine
Indicates that there is a shuttle service or route operating between the related entities.
- 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_69a252868de4819080e21c9938bfe8b6 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a258808ff08190a06b6206f635612b |
completed | Feb. 28, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69a256580c2c8190beecca60ca8595f3 |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a2587e598c81909e1082b813971f48 |
completed | Feb. 28, 2026, 2:52 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.