Triple
T1135389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 19th Street NW |
E23126
|
entity |
| Predicate | hasZoningAlong |
P727
|
FINISHED |
| Object | commercial properties |
—
|
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: commercial properties | Statement: [19th Street NW, hasZoningAlong, commercial properties]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasZoningAlong Context triple: [19th Street NW, hasZoningAlong, commercial properties]
-
A.
hasZone
Indicates that one entity possesses, contains, or is associated with a specific zone or designated area.
-
B.
hasNeighborhoodAlong
Indicates that one entity has a neighboring area or region that extends along the boundary or length of another entity.
-
C.
hasRailwayZone
Indicates that a location or railway entity falls under the jurisdiction or coverage area of a specific railway zone.
-
D.
zoningCharacter
chosen
Indicates how the regulatory or functional nature of a geographic area is defined or classified in terms of land-use zoning.
-
E.
hasFareZone
Indicates that an entity is located within or associated with a specific fare zone used for pricing or ticketing.
- 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_69a493ec75988190b63a11bafaec29b4 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4bde18d208190848c189b2b8d585f |
completed | March 1, 2026, 10:29 p.m. |
| PD | Predicate disambiguation | batch_69a4bb4b52d48190bec2e7ad1cc8efc0 |
completed | March 1, 2026, 10:18 p.m. |
Created at: March 1, 2026, 7:44 p.m.