Triple
T3370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Time Person of the Year |
E63
|
entity |
| Predicate | hasTypeOfRecipient |
P379
|
FINISHED |
| Object | individual person |
—
|
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: individual person | Statement: [Time Person of the Year, hasTypeOfRecipient, individual person]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfRecipient Context triple: [Time Person of the Year, hasTypeOfRecipient, individual person]
-
A.
hasMemberType
Indicates that an entity includes or is associated with members belonging to a specified type or category.
-
B.
notableRecipient
Indicates that an entity has received a notable award, honor, or recognition from another entity.
-
C.
hasCollectionType
Indicates that an entity is associated with or organized under a specific type or category of collection.
-
D.
hasRepresentationIn
Indicates that one entity is represented, depicted, or encoded within another entity, such as a concept, object, or data structure having a corresponding representation in a specific medium or context.
-
E.
hasInputType
Indicates that an entity takes another entity as its input type for its operation, function, or process.
- 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_69a238d6b47881909e68288aed2fd858 |
completed | Feb. 28, 2026, 12:37 a.m. |
| NER | Named-entity recognition | batch_69a23bcc8eb48190b897cc331563980a |
completed | Feb. 28, 2026, 12:50 a.m. |
| PD | Predicate disambiguation | batch_69a23994309081909ff3e869deef2156 |
completed | Feb. 28, 2026, 12:40 a.m. |
| PDg | Predicate description generation | batch_69a23bcb4bbc819093775f623998d62d |
completed | Feb. 28, 2026, 12:50 a.m. |
Created at: Feb. 28, 2026, 12:40 a.m.