Triple
T36829872
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | José Vasconcelos World Award of Education |
E910108
|
entity |
| Predicate | typicalLaureate |
P2730
|
FINISHED |
| Object | educator |
—
|
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: educator | Statement: [José Vasconcelos World Award of Education, typicalLaureate, educator]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalLaureate Context triple: [José Vasconcelos World Award of Education, typicalLaureate, educator]
-
A.
typicalLaureateType
chosen
Indicates the usual or most common type or category of laureate associated with something.
-
B.
hasLaureate
Indicates that an entity (such as an award or prize) has a specific person or group as its laureate or recipient.
-
C.
typicalHonoree
Indicates that an entity is the usual or characteristic recipient of an honor, award, or recognition associated with another entity.
-
D.
laureateOccupation
Indicates the professional role or field in which a laureate is recognized or has worked.
-
E.
typicalAwardedBy
Indicates the usual or standard agent (such as a person or organization) that confers or grants a particular award.
- 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_69f76e7e9d60819092442fba73290a46 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0e039481908a4a2666f76c5363 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:13 p.m.