Triple
T12238536
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Hampshire Route 101 |
E291664
|
entity |
| Predicate | freewaySegmentLocation |
P13550
|
FINISHED |
| Object | between Bedford and Hampton |
—
|
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: between Bedford and Hampton | Statement: [New Hampshire Route 101, freewaySegmentLocation, between Bedford and Hampton]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: freewaySegmentLocation Context triple: [New Hampshire Route 101, freewaySegmentLocation, between Bedford and Hampton]
-
A.
hasFreewaySegments
Indicates that one entity includes, contains, or is associated with specific freeway segments as part of its structure or network.
-
B.
highwaySectionName
Indicates the specific name assigned to a particular section or segment of a highway.
-
C.
isFreeway
Indicates that a given road segment functions as a freeway, typically designed for high-speed, limited-access vehicular traffic.
-
D.
servedByFreeway
chosen
Indicates that a location or area is directly accessed or connected by a freeway.
-
E.
rangeHighwayApprox
Indicates that one entity is approximately within the range or vicinity of a highway associated with another entity.
- 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_69d6ab67950c8190be08450a06228c4b |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d924a3973c8190a882046963b320fb |
completed | April 10, 2026, 4:26 p.m. |
| PD | Predicate disambiguation | batch_69d91c41bcbc81909782f4e3c571b218 |
completed | April 10, 2026, 3:50 p.m. |
Created at: April 8, 2026, 9:51 p.m.