Triple
T30708112
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Regency Centers |
E781808
|
entity |
| Predicate | propertyUseType |
P2529
|
FINISHED |
| Object | retail |
—
|
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: retail | Statement: [Regency Centers, propertyUseType, retail]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: propertyUseType Context triple: [Regency Centers, propertyUseType, retail]
-
A.
usageType
chosen
Indicates the specific manner, purpose, or context in which something is used or intended to be used.
-
B.
propUsed
Indicates that a particular property or attribute is utilized or applied in a given context or situation.
-
C.
propertiesType
Indicates that one entity is classified as a specific type or category of properties associated with another entity.
-
D.
partOfUse
Indicates that something functions as a component or constituent within the use or application of something else.
-
E.
usesProp
Indicates that one entity employs, utilizes, or makes use of a particular property, resource, or object in performing an action or fulfilling a function.
- 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_69f224abfcf081909492e64d3cc35262 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6c1265c208190aacd2b551f8f0f82 |
completed | May 3, 2026, 3:29 a.m. |
| PD | Predicate disambiguation | batch_69f6bd2415fc81908c23c311aebce66f |
completed | May 3, 2026, 3:12 a.m. |
Created at: April 29, 2026, 8:35 p.m.