Triple
T26494731
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Have with You to Saffron-Walden |
E669249
|
entity |
| Predicate | literaryFeudWith |
P167288
|
FINISHED |
| Object | Gabriel Harvey |
—
|
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: Gabriel Harvey | Statement: [Have with You to Saffron-Walden, literaryFeudWith, Gabriel Harvey]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: literaryFeudWith Context triple: [Have with You to Saffron-Walden, literaryFeudWith, Gabriel Harvey]
-
A.
literaryActivity
Indicates involvement in creating, studying, or engaging with written works such as literature, poetry, or scholarly texts.
-
B.
literaryAmbition
Indicates that an entity has the desire, intention, or drive to create, achieve, or succeed in the field of literature.
-
C.
literaryThemeInvolvement
Indicates the involvement or presence of a particular literary theme within a work, passage, or character arc.
-
D.
literaryMuseOf
Indicates a relationship in which one entity serves as the creative inspiration or muse for another entity’s literary work.
-
E.
literaryUniverse
Indicates that two or more works of literature exist within the same fictional universe or continuity, sharing settings, characters, or canonical events.
- 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_69eeb319007081909642b414b114b35a |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f66a6468ec8190a43ed6cd8c797f42 |
completed | May 2, 2026, 9:19 p.m. |
| PD | Predicate disambiguation | batch_69f66598d6008190a7ca8ff80399fd34 |
completed | May 2, 2026, 8:59 p.m. |
| PDg | Predicate description generation | batch_69f6691da93081909deaf680614fc900 |
completed | May 2, 2026, 9:14 p.m. |
Created at: April 27, 2026, 1:07 a.m.