Triple
T1256514
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vici Properties |
E12404
|
entity |
| Predicate | incomeType |
P24934
|
FINISHED |
| Object | contractual rental income |
—
|
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: contractual rental income | Statement: [Vici Properties, incomeType, contractual rental income]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: incomeType Context triple: [Vici Properties, incomeType, contractual rental income]
-
A.
salaryType
Indicates the classification or structure of compensation associated with an entity, such as whether pay is salaried, hourly, commission-based, or another type.
-
B.
employmentType
Indicates the specific kind or category of employment relationship that exists between an individual and an employer (e.g., full-time, part-time, contract).
-
C.
incomeMeasure
Indicates a relationship where one entity serves as a measure or metric of another entity’s income.
-
D.
economicStatus
Indicates the financial or socioeconomic condition or standing of an entity relative to others or to defined economic criteria.
-
E.
subjectOccupation
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
- F. None of above. chosen
Provenance (4 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_69a4933352e08190ac617291985e76c0 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4bfa8cfa08190ac49c437a94a843c |
completed | March 1, 2026, 10:37 p.m. |
| PD | Predicate disambiguation | batch_69a4bb6c977c8190a2bf3e8b67a59beb |
completed | March 1, 2026, 10:19 p.m. |
| PDg | Predicate description generation | batch_69a4bc4a1f048190bd1ddcc4cc3fe057 |
completed | March 1, 2026, 10:23 p.m. |
Created at: March 1, 2026, 7:50 p.m.