Triple
T12960333
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bianchon |
E310123
|
entity |
| Predicate | usedByAuthorAs |
P976
|
FINISHED |
| Object | linking figure across multiple novels |
—
|
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: linking figure across multiple novels | Statement: [Bianchon, usedByAuthorAs, linking figure across multiple novels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedByAuthorAs Context triple: [Bianchon, usedByAuthorAs, linking figure across multiple novels]
-
A.
usedByAuthor
Indicates that something (such as a method, tool, or resource) is employed or utilized by an author.
-
B.
usedByAuthorTo
Indicates that something is employed or utilized by an author to achieve a particular purpose or effect.
-
C.
hasAuthorOf
Indicates that one entity is the author or creator of another entity (such as a work, document, or publication).
-
D.
describedByAuthorAs
chosen
Indicates that one entity is characterized, labeled, or portrayed in a particular way by an author.
-
E.
hasAuthor
Indicates that an entity is written or created by a specific author.
- 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_69d7bdfb57a88190836b743e2825feca |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97e59a4c88190907d05b8d57dae89 |
completed | April 10, 2026, 10:48 p.m. |
| PD | Predicate disambiguation | batch_69d97dba57988190b786ffed55687a72 |
completed | April 10, 2026, 10:46 p.m. |
Created at: April 9, 2026, 5:44 p.m.