Triple
T249732
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UN Goodwill Ambassador |
E5116
|
entity |
| Predicate | hasSelectionCriteria |
P136
|
FINISHED |
| Object | professional achievements |
—
|
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: professional achievements | Statement: [UN Goodwill Ambassador, hasSelectionCriteria, professional achievements]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSelectionCriteria Context triple: [UN Goodwill Ambassador, hasSelectionCriteria, professional achievements]
-
A.
selectionCriteria
chosen
Indicates the conditions or rules used to choose certain entities from a larger set.
-
B.
hasCriterionType
Indicates that something is associated with or classified by a specific type of criterion used for evaluation or decision-making.
-
C.
hasCondition
Indicates that an entity possesses, experiences, or is affected by a particular condition or state.
-
D.
hasRefinement
Indicates that one entity represents a more detailed, specific, or improved version of another entity.
-
E.
hasSelectionBody
Indicates that an entity includes or is associated with a specific selection body, i.e., the defined content or portion that has been selected.
- 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_69a257c4bf688190a46ebbf411ab7473 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25d3728f0819086214ccc2db2305a |
completed | Feb. 28, 2026, 3:12 a.m. |
| PD | Predicate disambiguation | batch_69a25b665f8c8190aac6fcbba2a0eebb |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:54 a.m.