Triple
T36114328
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Broadway production of Rodgers & Hammerstein's Cinderella |
E1044578
|
entity |
| Predicate | featuresOriginalBookBy |
P40446
|
FINISHED |
| Object | Oscar Hammerstein II |
E12356
|
NE 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: Oscar Hammerstein II | Statement: [Broadway production of Rodgers & Hammerstein's Cinderella, featuresOriginalBookBy, Oscar Hammerstein II]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresOriginalBookBy Context triple: [Broadway production of Rodgers & Hammerstein's Cinderella, featuresOriginalBookBy, Oscar Hammerstein II]
-
A.
bookAppearance
Indicates that an entity’s visual or physical characteristics as presented in a book are being described or referenced.
-
B.
book4Covers
Indicates that one entity is the front or outer covering (such as a dust jacket or protective layer) of a book.
-
C.
bookCharacteristic
Indicates that a particular characteristic, feature, or attribute is associated with a given book.
-
D.
book2Covers
Indicates that one entity (typically a book) has another entity as its cover or is associated with a specific cover representation.
-
E.
featuresAuthor
chosen
Indicates that something includes or highlights a particular author as a primary associated contributor.
- F. None of above.
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_69f76e344a4c8190af3858c6d78ba88f |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c8d06cc8190ab6a5e18d9d2571e |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a38de06a8cc819097592fecbda08fcc |
completed | June 22, 2026, 7:02 a.m. |
| PD | Predicate disambiguation | batch_6a037a0895b48190acdd88dc10db7be7 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:08 p.m.