Triple
T37119850
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | L’Enfant Plan |
E919215
|
entity |
| Predicate | avenueIncludes |
P73526
|
FINISHED |
| Object | Pennsylvania Avenue |
—
|
NE NERFINISHED |
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: Pennsylvania Avenue | Statement: [L’Enfant Plan, avenueIncludes, Pennsylvania Avenue]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: avenueIncludes Context triple: [L’Enfant Plan, avenueIncludes, Pennsylvania Avenue]
-
A.
servesAvenue
Indicates that something (such as a service, route, or facility) provides service to or operates along a particular avenue.
-
B.
avenueRadiatingFrom
Indicates that one avenue extends outward from and is oriented away from another central point or thoroughfare, like a spoke radiating from a hub.
-
C.
roadCorridorIncludes
chosen
Indicates that a specified road corridor spatially contains or encompasses another element or segment within its defined bounds.
-
D.
concessionIncludes
Indicates that one concession contains, comprises, or encompasses another concession as a part or subset.
-
E.
usesStateNamedAvenues
Indicates that an entity makes use of avenues whose names are derived from or correspond to the names of states.
- 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_69f76e9c57148190ba789dd059645bb9 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb344c60f8819090f2e21e1e61d621 |
completed | May 6, 2026, 12:30 p.m. |
| PD | Predicate disambiguation | batch_69fb2f642db08190b562725502c74ea6 |
completed | May 6, 2026, 12:09 p.m. |
Created at: May 3, 2026, 4:15 p.m.