Triple
T31609161
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jaan Poska (memorial) |
E806578
|
entity |
| Predicate | subjectOccupationOfHonouree |
P18120
|
FINISHED |
| Object | statesman |
—
|
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: statesman | Statement: [Jaan Poska (memorial), subjectOccupationOfHonouree, statesman]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subjectOccupationOfHonouree Context triple: [Jaan Poska (memorial), subjectOccupationOfHonouree, statesman]
-
A.
honouredPersonOccupation
chosen
Indicates that the honored person is or was associated with a particular occupation or professional role.
-
B.
laureateOccupation
Indicates the professional role or field in which a laureate is recognized or has worked.
-
C.
eraOfOccupation
Indicates the time period during which an occupation or role was held or practiced.
-
D.
namedPersonOccupation
Indicates that a person is explicitly identified as having a particular occupation or job role.
-
E.
honoreeRole
Indicates the specific role, title, or capacity in which an individual is being honored in relation to an award, event, or recognition.
- 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_69f348d61f2081908cad94bc9ffbb671 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f7be53890081909b1d93f30a8f31c6 |
completed | May 3, 2026, 9:29 p.m. |
| PD | Predicate disambiguation | batch_69f7bccacbac8190978976324c67db28 |
completed | May 3, 2026, 9:23 p.m. |
Created at: April 30, 2026, 10:36 p.m.