Triple
T10007499
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Waitress (musical) |
E198288
|
entity |
| Predicate | tonyCategoryNomination |
P36383
|
FINISHED |
| Object | Best Musical |
—
|
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: Best Musical | Statement: [Waitress (musical), tonyCategoryNomination, Best Musical]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tonyCategoryNomination Context triple: [Waitress (musical), tonyCategoryNomination, Best Musical]
-
A.
tonyNominations
chosen
Indicates that an entity has received one or more nominations for a Tony Award.
-
B.
tonyNominationsCount
Indicates the number of Tony Award nominations an entity has received.
-
C.
nominatedIn
Indicates that an entity has been formally put forward as a candidate for an award, position, or recognition within a specific event, context, or time period.
-
D.
tonyAwardsWonFor
Indicates the specific Tony Award-winning work or role for which an entity received a Tony Award.
-
E.
academyAwardNominations
Indicates that an entity has received one or more nominations for an Academy Award (Oscars).
- 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_69ca830fcca48190bbbd9b20c233835f |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cdcd187fe481908556ea896c528ea4 |
completed | April 2, 2026, 1:57 a.m. |
| PD | Predicate disambiguation | batch_69cd1da2cf9081908a6c0eb5247d0bc2 |
completed | April 1, 2026, 1:29 p.m. |
Created at: March 30, 2026, 8:52 p.m.