Triple
T1978523
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marquisate of Dalí de Púbol |
E42970
|
entity |
| Predicate | titleHolderProfession |
P33026
|
FINISHED |
| Object | painter |
—
|
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: painter | Statement: [Marquisate of Dalí de Púbol, titleHolderProfession, painter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: titleHolderProfession Context triple: [Marquisate of Dalí de Púbol, titleHolderProfession, painter]
-
A.
namedPersonOccupation
Indicates that a person is explicitly identified as having a particular occupation or job role.
-
B.
authorOccupation
Indicates the professional role or job that an author holds or is associated with.
-
C.
titleHolderFullName
Indicates the full personal name of the entity that holds a particular title or position.
-
D.
titleHolderTo
Indicates that one entity currently holds or possesses an official title, position, or designation in relation to another entity.
-
E.
titleHolderFrom
Indicates that an entity holds or has held a specific title or position starting from a given point in time.
- 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_69a8871289048190b00b0d7744b7b2b1 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb43011188190b6a41c004e9e4802 |
completed | March 7, 2026, 5:14 a.m. |
| PD | Predicate disambiguation | batch_69abaff9a09c8190a81fa13f4b85bc79 |
completed | March 7, 2026, 4:56 a.m. |
| PDg | Predicate description generation | batch_69abb09b27e88190bff164040fef6d7e |
completed | March 7, 2026, 4:59 a.m. |
Created at: March 4, 2026, 7:36 p.m.