Triple
T3100543
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trump Management |
E64704
|
entity |
| Predicate | targetTenants |
P10541
|
FINISHED |
| Object | working-class 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: working-class tenants | Statement: [Trump Management, targetTenants, working-class tenants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetTenants Context triple: [Trump Management, targetTenants, working-class tenants]
-
A.
hasTenants
Indicates that an entity occupies or rents space from another entity as its tenant.
-
B.
tenantsFrom
Indicates that one or more tenants originate from, are associated with, or are derived from a specified source entity.
-
C.
targetsGroup
chosen
Indicates that an action, influence, or effect is directed toward a specific group as its intended recipient or focus.
-
D.
numberOfAnchorTenants
Indicates the count of primary or major tenants associated with a given property or location.
-
E.
mainTenant
Indicates that the subject is the primary tenant responsible for a property or rental agreement, as opposed to a subtenant or secondary occupant.
- 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_69ad857dc98481909e585dc3372e3ed5 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada26b03a081909cf187b9a8f805ce |
completed | March 8, 2026, 4:23 p.m. |
| PD | Predicate disambiguation | batch_69ad9df06ed88190809f0683122caa5a |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:03 p.m.