Triple
T499154
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BAFTA Award for Best Actor in a Leading Role |
E10360
|
entity |
| Predicate | hasAwardedSince |
P11365
|
FINISHED |
| Object | 1950s |
—
|
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: 1950s | Statement: [BAFTA Award for Best Actor in a Leading Role, hasAwardedSince, 1950s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAwardedSince Context triple: [BAFTA Award for Best Actor in a Leading Role, hasAwardedSince, 1950s]
-
A.
hasAwarded
Indicates that one entity has given or conferred an award to another entity.
-
B.
awardedSince
chosen
Indicates that an entity has been receiving a particular award continuously from a specified starting time onward.
-
C.
awardedDuring
Indicates that an award or honor was given to an entity within a specified time period or event.
-
D.
lastAwarded
Indicates the most recent time or instance at which an entity received a particular award.
-
E.
hasAwardedDiscipline
Indicates that one entity has formally imposed or granted a disciplinary action or sanction upon another entity.
- 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_69a2e847df8481909239ec08ccf1e376 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f119b14c8190a5a6b119579c2682 |
completed | Feb. 28, 2026, 1:43 p.m. |
| PD | Predicate disambiguation | batch_69a2edfa87cc8190a77c726a5a55b7d9 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.