Triple
T346653
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meriden, Connecticut |
E6956
|
entity |
| Predicate | hasHighwayJunction |
P1018
|
FINISHED |
| Object | junction of I-91 and I-691 |
—
|
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: junction of I-91 and I-691 | Statement: [Meriden, Connecticut, hasHighwayJunction, junction of I-91 and I-691]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHighwayJunction Context triple: [Meriden, Connecticut, hasHighwayJunction, junction of I-91 and I-691]
-
A.
roadJunctionIncludes
Indicates that a road junction spatially contains or encompasses a specific road segment or related roadway element as part of its structure.
-
B.
hasMajorHighway
Indicates that a location or area is served by or directly connected to a major highway route.
-
C.
hasJunctionWith
chosen
Indicates that one entity meets or intersects with another at a shared junction point.
-
D.
roadFeature
Indicates that an entity is a specific physical or functional characteristic associated with a road, such as its structure, markings, or related infrastructure.
-
E.
hasApproachRoad
Indicates that one entity is connected to or accessed by another entity via an approach road leading to it.
- 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_69a2e7951ba08190960e90823b5078f3 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2eb1a37c08190b1380f6bf8513a37 |
completed | Feb. 28, 2026, 1:18 p.m. |
| PD | Predicate disambiguation | batch_69a2e95451a4819090f4e4fb9b21a493 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.