Triple
T41402
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rosslyn |
E815
|
entity |
| Predicate | hasZoningType |
P727
|
FINISHED |
| Object | high-density commercial |
—
|
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: high-density commercial | Statement: [Rosslyn, hasZoningType, high-density commercial]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasZoningType Context triple: [Rosslyn, hasZoningType, high-density commercial]
-
A.
zoningCharacter
chosen
Indicates how the regulatory or functional nature of a geographic area is defined or classified in terms of land-use zoning.
-
B.
hasFareZone
Indicates that an entity is located within or associated with a specific fare zone used for pricing or ticketing.
-
C.
hasBoundaryType
Indicates that one entity has a boundary characterized by a specific type or classification in relation to another entity or context.
-
D.
regionType
Indicates the classification or category of a region, specifying what kind of region it is (e.g., administrative, geographic, or functional).
-
E.
hasProtectedArea
Indicates that an entity possesses, includes, or is associated with a designated protected area for conservation or restricted use.
- 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_69a247a8f6c08190bac804906d62ed5a |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a24db9527c8190816b6b25c88cb2f4 |
completed | Feb. 28, 2026, 2:06 a.m. |
| PD | Predicate disambiguation | batch_69a24ab8a8908190beec6da6694dd4c9 |
completed | Feb. 28, 2026, 1:54 a.m. |
Created at: Feb. 28, 2026, 1:46 a.m.