Triple
T6747885
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Inner Loop |
E154263
|
entity |
| Predicate | connectsSuburbsIn |
P46405
|
FINISHED |
| Object | Maryland suburbs of Washington, D.C. |
—
|
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: Maryland suburbs of Washington, D.C. | Statement: [Inner Loop, connectsSuburbsIn, Maryland suburbs of Washington, D.C.]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: connectsSuburbsIn Context triple: [Inner Loop, connectsSuburbsIn, Maryland suburbs of Washington, D.C.]
-
A.
connectsToSuburb
Indicates that one entity has a direct connection or link to a suburban area, such as via transport, infrastructure, or adjacency.
-
B.
connectsCityTo
Indicates a relationship in which a route, infrastructure, or link joins one city to another, enabling connection or interaction between them.
-
C.
connectsCity
Indicates a relationship where one entity serves as a link or route that joins or provides direct access between two cities.
-
D.
connectsCityIndirectly
Indicates that one location is linked to a city through one or more intermediate locations or routes, rather than by a direct connection.
-
E.
servesSuburbsOf
chosen
Indicates that a service, route, or facility provides coverage or support to the suburban areas associated with a particular city or region.
- 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_69c6880ef37881909268a5a7299b9293 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d327e37081909d576e6eff9eec97 |
completed | March 27, 2026, 6:57 p.m. |
| PD | Predicate disambiguation | batch_69c6d09227108190b253b91967831a85 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:11 p.m.