Triple
T31417685
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York Musical Theatre Festival |
E801436
|
entity |
| Predicate | notableAlumniWork |
P26239
|
FINISHED |
| Object | Next to Normal |
E45783
|
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: Next to Normal | Statement: [New York Musical Theatre Festival, notableAlumniWork, Next to Normal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableAlumniWork Context triple: [New York Musical Theatre Festival, notableAlumniWork, Next to Normal]
-
A.
notableAlumniAchievement
Indicates that an alumnus is recognized for a significant achievement or distinction associated with their post-graduation activities.
-
B.
hasNotableAlumniType
Indicates that an entity has notable alumni belonging to a specified category or type.
-
C.
notableWorkWith
chosen
Indicates a relationship where two or more entities are recognized for having collaborated on or been jointly associated with a significant work or project.
-
D.
notableAlumniRegion
Indicates that a region is known for having produced notable alumni associated with a particular institution or organization.
-
E.
notableAlumniCareerPath
Indicates the professional trajectories or career developments followed by notable alumni after their association with an institution or organization.
- 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_69f348c26f048190b4adadd71b4596c5 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_6a037c876524819098545e6037d3107d |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a2e8a136c0481908e709b0c222d4d85 |
completed | June 14, 2026, 11:01 a.m. |
| PD | Predicate disambiguation | batch_6a0379e5174c8190a0bdde7e381b7624 |
completed | May 12, 2026, 7:05 p.m. |
Created at: April 30, 2026, 8:45 p.m.