Triple
T32630605
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Smash (novel) |
E834195
|
entity |
| Predicate | hasAuthorExperienceIn |
P115636
|
FINISHED |
| Object | Broadway theatre |
—
|
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: Broadway theatre | Statement: [Smash (novel), hasAuthorExperienceIn, Broadway theatre]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAuthorExperienceIn Context triple: [Smash (novel), hasAuthorExperienceIn, Broadway theatre]
-
A.
hasExperienceOf
Indicates that one entity has undergone, encountered, or lived through a particular event, situation, or activity associated with another entity.
-
B.
hasPastExperience
Indicates that an entity has previously engaged in or undergone the specified activity, role, or situation in the past.
-
C.
hasNotableExperience
Indicates that an entity has a significant or distinguished experience related to another entity or context.
-
D.
hasIntendedExperience
Indicates that an entity is meant or designed to undergo a particular experience or mental state.
-
E.
relatedToAuthorExperience
chosen
Indicates that something has a connection to, is influenced by, or is derived from the author's personal experiences.
- 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_69f3492dc2308190a88c6e30a3f3f576 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fbc36ce1f88190a7fa1656b714e107 |
completed | May 6, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69fbbd13595c81908719f52c3d37a7e8 |
completed | May 6, 2026, 10:13 p.m. |
Created at: May 1, 2026, 1:07 a.m.