Triple
T7582651
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Melvin Simon & Associates |
E179526
|
entity |
| Predicate | developedPropertyType |
P68886
|
FINISHED |
| Object | regional shopping malls |
—
|
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: regional shopping malls | Statement: [Melvin Simon & Associates, developedPropertyType, regional shopping malls]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: developedPropertyType Context triple: [Melvin Simon & Associates, developedPropertyType, regional shopping malls]
-
A.
propertyTypeOwned
Indicates that one entity owns a specific type or category of property in relation to another entity.
-
B.
architectureProperty
Indicates that a specified architectural characteristic or feature is attributed to, or associated with, an entity.
-
C.
residenceType
Indicates the kind or category of dwelling or living arrangement associated with an entity.
-
D.
realEstateCategory
Indicates the classification of a property into a specific type or category within real estate (e.g., residential, commercial, industrial).
-
E.
propertyType_dtx
chosen
Indicates that one entity has a specific type or category of property in relation to another entity.
- 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_69c69f327db881909a21ae3b156f8ded |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c6f978341081909e009c410ffc5039 |
completed | March 27, 2026, 9:41 p.m. |
| PD | Predicate disambiguation | batch_69c6f4e04c2c8190a889d928515d9b8e |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:52 p.m.