Triple
T28188190
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Japanese honors system |
E716232
|
entity |
| Predicate | mainAwardSeasons |
P169276
|
FINISHED |
| Object | spring |
—
|
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: spring | Statement: [Japanese honors system, mainAwardSeasons, spring]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainAwardSeasons Context triple: [Japanese honors system, mainAwardSeasons, spring]
-
A.
associatedAwardWinningShow
Indicates that an entity is linked to a show that has received an award.
-
B.
tonyNominations
Indicates that an entity has received one or more nominations for a Tony Award.
-
C.
hasAwardShow
Indicates that an entity organizes, hosts, or is associated with a specific award show or ceremony.
-
D.
academyAwardsContext
Indicates the relationship between an entity and its context or details specifically related to the Academy Awards (e.g., nominations, wins, categories, or years).
-
E.
academyAwardNominations
Indicates that an entity has received one or more nominations for an Academy Award (Oscars).
- 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_69efd6b612f48190a72012b520afbd10 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69f67d691a948190afa7fb19ae7d4ac5 |
completed | May 2, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69f678cc272081909e5c70f1bc7407f0 |
completed | May 2, 2026, 10:21 p.m. |
| PDg | Predicate description generation | batch_69f67c9ec1708190b26ccf402ed7b106 |
completed | May 2, 2026, 10:37 p.m. |
Created at: April 27, 2026, 10:24 p.m.