Triple
T15905742
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jonathan Flynn |
E385706
|
entity |
| Predicate | literaryAmbition |
P120999
|
FINISHED |
| Object | to write a great American book |
—
|
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: to write a great American book | Statement: [Jonathan Flynn, literaryAmbition, to write a great American book]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: literaryAmbition Context triple: [Jonathan Flynn, literaryAmbition, to write a great American book]
-
A.
literaryActivity
Indicates involvement in creating, studying, or engaging with written works such as literature, poetry, or scholarly texts.
-
B.
literaryMuseOf
Indicates a relationship in which one entity serves as the creative inspiration or muse for another entity’s literary work.
-
C.
literaryUniverse
Indicates that two or more works of literature exist within the same fictional universe or continuity, sharing settings, characters, or canonical events.
-
D.
literarySubject
Indicates that one entity serves as the subject, topic, or focus of a literary work created by another entity.
-
E.
literaryInterest
Indicates that one entity has an interest in, appreciation of, or engagement with the literary works or writings of another entity.
- 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_69d86da686e4819097cbf3b1fc2d881d |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e17d4d08f481909f38b75e3f42d9ab |
completed | April 17, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69e142ca3b208190946c3aa4c1e6087c |
completed | April 16, 2026, 8:12 p.m. |
| PDg | Predicate description generation | batch_69e17d48cc9c8190b03fd07ae2e9dfd8 |
completed | April 17, 2026, 12:22 a.m. |
Created at: April 10, 2026, 4:52 a.m.