Triple
T36114327
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Broadway production of Rodgers & Hammerstein's Cinderella |
E1044578
|
entity |
| Predicate | featuresAdditionalBookMaterialBy |
P32920
|
FINISHED |
| Object | Douglas Carter Beane |
E1055684
|
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: Douglas Carter Beane | Statement: [Broadway production of Rodgers & Hammerstein's Cinderella, featuresAdditionalBookMaterialBy, Douglas Carter Beane]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresAdditionalBookMaterialBy Context triple: [Broadway production of Rodgers & Hammerstein's Cinderella, featuresAdditionalBookMaterialBy, Douglas Carter Beane]
-
A.
additionalMaterialBy
chosen
Indicates that one entity serves as supplementary or supporting material created by a specified agent or source.
-
B.
hasEducationalMaterial
Indicates that an entity provides, contains, or is associated with educational content or learning resources for another entity.
-
C.
featuresMaterialFrom
Indicates that one entity incorporates, contains, or is composed of material originating from another entity.
-
D.
book4Subject
Indicates that something is the subject or topic that a particular book is about.
-
E.
libraryCatalog
Indicates a relationship where a library’s catalog system organizes, indexes, and provides access information for the items held in the library’s collection.
- 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_6a390d3c32b481909441aa4809937988 |
completed | June 22, 2026, 10:23 a.m. |
| PD | Predicate disambiguation | batch_6a037a0895b48190acdd88dc10db7be7 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:08 p.m.