Triple
T41439
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clarendon |
E816
|
entity |
| Predicate | zoning |
P727
|
FINISHED |
| Object | mixed commercial and residential |
—
|
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: mixed commercial and residential | Statement: [Clarendon, zoning, mixed commercial and residential]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: zoning Context triple: [Clarendon, zoning, mixed commercial and residential]
-
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.
zone
Indicates that an entity is located within, associated with, or assigned to a particular geographic or conceptual area or zone.
-
C.
legalArea
Indicates the specific field or branch of law that a legal matter, case, or document pertains to.
-
D.
area
Indicates that one entity has a measured two-dimensional extent or surface size quantified by another entity.
-
E.
neighborhood
Indicates that one entity is located in close spatial proximity to another, typically within the same local area or district.
- 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.