Triple
T9069035
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tonight |
E217314
|
entity |
| Predicate | associatedWorkType |
P86785
|
FINISHED |
| Object | Broadway 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: Broadway musical | Statement: [Tonight, associatedWorkType, Broadway musical]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWorkType Context triple: [Tonight, associatedWorkType, Broadway musical]
-
A.
associatedWork
Indicates that there exists a related or connected work (such as a publication, creative piece, or project) that is meaningfully linked to the subject.
-
B.
workTypeContributedTo
Indicates that an entity contributed to the creation, development, or production of a particular type of work.
-
C.
workRelatedTo
Indicates a relationship where one entity’s work, tasks, or professional activities are connected, associated, or relevant to those of another entity.
-
D.
associatedWithWorkforce
Indicates a relationship in which an entity is connected or related to a particular workforce, such as its members, activities, or management.
-
E.
associatedWithWorkTheme
Indicates a relationship where something is connected or related to a particular work theme or subject matter.
- 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_69ca83d5a7f48190b16c1e59bd43ede0 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc955ba250819085fa49e0059d06c1 |
completed | April 1, 2026, 3:47 a.m. |
| PD | Predicate disambiguation | batch_69cc65f881248190bfd220bb28a9fb5f |
completed | April 1, 2026, 12:25 a.m. |
| PDg | Predicate description generation | batch_69cc668ad3d881908a8a93a6a1d553e4 |
completed | April 1, 2026, 12:27 a.m. |
Created at: March 30, 2026, 7:11 p.m.