Triple
T9435724
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sigourney Street |
E227499
|
entity |
| Predicate | hasRoadEnvironment |
P47160
|
FINISHED |
| Object | mixed-use urban corridor |
—
|
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: mixed-use urban corridor | Statement: [Sigourney Street, hasRoadEnvironment, mixed-use urban corridor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRoadEnvironment Context triple: [Sigourney Street, hasRoadEnvironment, mixed-use urban corridor]
-
A.
roadEnvironment
chosen
Indicates that the relationship or action occurs within, is influenced by, or is specifically associated with a road or roadway environment.
-
B.
hasRoadCondition
Indicates that a specified road segment possesses or is characterized by a particular condition or state (e.g., quality, surface, or status).
-
C.
hasRoadComponent
Indicates that something includes, contains, or is composed of a specific road-related part or element.
-
D.
hasRoadway
Indicates that one location or area is connected to another by a road or roadway infrastructure.
-
E.
hasRoadStandard
Indicates that a road or roadway segment conforms to, or is governed by, a specific road design, construction, or operational standard.
- 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_69ca8437a7ac81908651de48f2d2141d |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd7e64109081908222f590928bc572 |
completed | April 1, 2026, 8:21 p.m. |
| PD | Predicate disambiguation | batch_69cca55548488190b171ae695a3212de |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:50 p.m.