Triple
T36114375
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Broadway production of Rodgers & Hammerstein's Cinderella |
E1044578
|
entity |
| Predicate | receivedTonyAwardFor |
P16597
|
FINISHED |
| Object | Best Costume Design of a 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 Costume Design of a Musical | Statement: [Broadway production of Rodgers & Hammerstein's Cinderella, receivedTonyAwardFor, Best Costume Design of a Musical]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: receivedTonyAwardFor Context triple: [Broadway production of Rodgers & Hammerstein's Cinderella, receivedTonyAwardFor, Best Costume Design of a Musical]
-
A.
hasTonyAward
Indicates that an entity has received or been awarded a Tony Award.
-
B.
tonyAwardsWonFor
chosen
Indicates the specific Tony Award-winning work or role for which an entity received a Tony Award.
-
C.
sharedTonyAwardWith
Indicates that two entities have both received a Tony Award in the same year and category, or were otherwise jointly recognized with a Tony Award.
-
D.
numberOfTonyAwards
Indicates the total count of Tony Awards that an entity has received.
-
E.
emmyAwardFor
Indicates that an entity has received or is associated with a specific Emmy Award for a particular work or achievement.
- 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_69f76e344a4c8190af3858c6d78ba88f |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fbc36ce1f88190a7fa1656b714e107 |
completed | May 6, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69fbbd13595c81908719f52c3d37a7e8 |
completed | May 6, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:08 p.m.