Triple
T34554670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rosie Dunne |
E887168
|
entity |
| Predicate | dreamOccupation |
P104631
|
FINISHED |
| Object | hotelier |
—
|
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: hotelier | Statement: [Rosie Dunne, dreamOccupation, hotelier]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dreamOccupation Context triple: [Rosie Dunne, dreamOccupation, hotelier]
-
A.
dreamJob
Indicates that one entity is the ideal or highly desired job or occupation of another entity.
-
B.
occupationAspiration
chosen
Indicates a person's desired or intended future occupation or career goal.
-
C.
visionaryOccupation
Indicates that an entity holds an occupation or role characterized by forward-thinking, innovative, or visionary activities or responsibilities.
-
D.
subjectOccupation
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
-
E.
fictionalOccupation
Indicates that one entity is the imaginary or narrative-based job, role, or profession attributed to another entity within a fictional context.
- 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_69f349cff89081908f91e0b064f4833e |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f7202aeed481909561610c17c91458 |
completed | May 3, 2026, 10:15 a.m. |
| PD | Predicate disambiguation | batch_69f71cc8074c81909ae09bea2acf1a09 |
completed | May 3, 2026, 10 a.m. |
Created at: May 1, 2026, 2:02 a.m.