Triple
T9357994
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chapter XIX: Zenobia’s Drawing-Room |
E225194
|
entity |
| Predicate | fictionalWorkOfGenre |
P69182
|
FINISHED |
| Object | novel chapter |
—
|
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: novel chapter | Statement: [Chapter XIX: Zenobia’s Drawing-Room, fictionalWorkOfGenre, novel chapter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalWorkOfGenre Context triple: [Chapter XIX: Zenobia’s Drawing-Room, fictionalWorkOfGenre, novel chapter]
-
A.
fictionalGenre
chosen
Indicates that a work of fiction belongs to or is categorized under a particular narrative genre or style.
-
B.
fictionalMedium
Indicates that a work of fiction is presented or conveyed through a particular medium or format (such as a book, film, game, or comic).
-
C.
workInFiction
Indicates that one entity is a fictional work in which the other entity appears or is set.
-
D.
literaryGenreOfWork
Indicates that a work belongs to or is classified under a particular literary genre.
-
E.
fictionalOrigin
Indicates that one entity originates from, or was first introduced within, a fictional work, universe, or narrative created by another entity.
- 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_69ca842bdd648190904131d58620d448 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd4ff06608819086e9f11789beaf22 |
completed | April 1, 2026, 5:03 p.m. |
| PD | Predicate disambiguation | batch_69cc7a68ab9481909f97cb70764697cc |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:42 p.m.