Triple
T3383979
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Federal Realty Investment Trust |
E71251
|
entity |
| Predicate | primaryTenantType |
P18037
|
FINISHED |
| Object | Retail tenants |
—
|
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 tenants | Statement: [Federal Realty Investment Trust, primaryTenantType, Retail tenants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryTenantType Context triple: [Federal Realty Investment Trust, primaryTenantType, Retail tenants]
-
A.
primaryTenantTo
Indicates that one entity serves as the main or principal tenant in relation to another entity, such as a property or lease.
-
B.
primaryTenantFrom
Indicates that one entity serves as the main or principal tenant associated with another entity (such as a property or lease).
-
C.
mainTenant
Indicates that the subject is the primary tenant responsible for a property or rental agreement, as opposed to a subtenant or secondary occupant.
-
D.
tenantType
chosen
Indicates the classification or category of a tenant in a tenancy or rental relationship.
-
E.
primaryTargetType
Indicates the main category or type of entity that is the principal focus or intended recipient of an action, effect, or operation.
- 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_69ad85a8fd9c819095ecedf838d2bf1b |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb5ec85d08190b28110157c39435f |
completed | March 8, 2026, 5:46 p.m. |
| PD | Predicate disambiguation | batch_69ada434bae48190a77ea37f9274ad8f |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:14 p.m.