Triple
T12747603
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. President |
E304645
|
entity |
| Predicate | addressedPersonHoldsTitle |
P106701
|
FINISHED |
| Object | President of Austria |
—
|
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: President of Austria | Statement: [Mr. President, addressedPersonHoldsTitle, President of Austria]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: addressedPersonHoldsTitle Context triple: [Mr. President, addressedPersonHoldsTitle, President of Austria]
-
A.
officeHolderTitle
Indicates the official position or title held by a person in an office or role.
-
B.
holderFullTitle
Indicates that one entity is the complete, formal title or designation held by another entity.
-
C.
typicalOfficeHolderTitle
Indicates the standard or commonly used title typically held by the office holder of a given position or role.
-
D.
titleHeldAs
Indicates that an entity holds or possesses a specific title in a particular capacity or role.
-
E.
officeHolderMayUseTitle
Indicates that a person who holds a particular office is permitted to use a specified official title.
- 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_69d7bdf1426c8190a4402e1c4cdec33a |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96d89ea70819098c470344f172167 |
completed | April 10, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69d96406e97c8190b79081039847115c |
completed | April 10, 2026, 8:56 p.m. |
| PDg | Predicate description generation | batch_69d96d87078c819083ea724238992204 |
completed | April 10, 2026, 9:37 p.m. |
Created at: April 9, 2026, 5:27 p.m.