Triple
T23211659
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northwest street numbering system of Washington, D.C. |
E580608
|
entity |
| Predicate | northSouthStreetsNamingPattern |
P36245
|
FINISHED |
| Object | ordinal numbers |
—
|
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: ordinal numbers | Statement: [Northwest street numbering system of Washington, D.C., northSouthStreetsNamingPattern, ordinal numbers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: northSouthStreetsNamingPattern Context triple: [Northwest street numbering system of Washington, D.C., northSouthStreetsNamingPattern, ordinal numbers]
-
A.
hasStreetNamingPattern
chosen
Indicates that there is a characteristic or systematic way in which streets are named in relation to a given entity.
-
B.
streetPatternNamedFor
Indicates that a street pattern or layout is named in honor of, or derived from, a particular entity.
-
C.
northSouthRoutes
Indicates that there are routes or connections running in a generally north–south direction between the related entities.
-
D.
northSouthAxis
Indicates a spatial or directional relationship aligned along the north–south axis between entities.
-
E.
roadDirectionConvention
Indicates the customary rule in a place for which side of the road vehicles are expected to drive on.
- 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_69e24602ae1481908aaa6bc7ca493867 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f191620378819096362252c3b819b6 |
completed | April 29, 2026, 5:04 a.m. |
| PD | Predicate disambiguation | batch_69effcccee508190a7ae311fdd319806 |
completed | April 28, 2026, 12:18 a.m. |
Created at: April 17, 2026, 4:07 p.m.