Triple
T26385414
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rent (musical) |
E663263
|
entity |
| Predicate | authorDeathRelatedFact |
P12931
|
FINISHED |
| Object | Jonathan Larson died the day of the Off-Broadway premiere |
—
|
NE NERFINISHED |
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: Jonathan Larson died the day of the Off-Broadway premiere | Statement: [Rent (musical), authorDeathRelatedFact, Jonathan Larson died the day of the Off-Broadway premiere]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: authorDeathRelatedFact Context triple: [Rent (musical), authorDeathRelatedFact, Jonathan Larson died the day of the Off-Broadway premiere]
-
A.
dateOfDeath
Indicates the specific date on which an individual or entity died.
-
B.
notableDeath
chosen
Indicates that an entity’s death is considered significant or noteworthy in some context.
-
C.
reasonForDeath
Indicates the cause, circumstance, or condition that led to an entity’s death.
-
D.
notableDeathMethod
Indicates the manner or method by which an entity (typically a person) died, especially when that cause of death is historically or culturally notable.
-
E.
legendaryCauseOfDeath
Indicates a legendary or mythic account of how an entity died, as opposed to a historically verified cause of death.
- 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_69ee88374adc81909868f3bab374a32f |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69f6a8df16a88190a23820e64a3b1f92 |
completed | May 3, 2026, 1:46 a.m. |
| PD | Predicate disambiguation | batch_69f6a751d5e48190a77dcecbe7ef9f0b |
completed | May 3, 2026, 1:39 a.m. |
Created at: April 26, 2026, 11:22 p.m.