Triple
T34122622
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Town of Foxfield, Colorado |
E875184
|
entity |
| Predicate | landUseFocus |
P162036
|
FINISHED |
| Object | 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: residential | Statement: [Town of Foxfield, Colorado, landUseFocus, residential]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: landUseFocus Context triple: [Town of Foxfield, Colorado, landUseFocus, residential]
-
A.
landUseEmphasis
chosen
Indicates the primary type or focus of how a piece of land is used or intended to be used (e.g., residential, commercial, agricultural).
-
B.
landUseContext
Indicates the contextual setting or circumstances under which a particular piece of land is used or designated for a specific purpose.
-
C.
majorLandUse
Indicates the primary way a given area of land is utilized or designated (e.g., residential, commercial, agricultural).
-
D.
primaryLandUse
Indicates the main or dominant way in which a given piece of land is utilized or designated (e.g., residential, agricultural, commercial).
-
E.
landUseIncludes
Indicates that a specified land area contains or permits the specified type(s) of land use within its boundaries.
- 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_69f349a9271c81909576994c9ef7b179 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f70fb4f18c819099ef6d9177b7d205 |
completed | May 3, 2026, 9:04 a.m. |
| PD | Predicate disambiguation | batch_69f70f3a54d481909ba6bdda3647b761 |
completed | May 3, 2026, 9:02 a.m. |
Created at: May 1, 2026, 1:53 a.m.