Triple
T14641626
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Book Two: Jacob |
E343736
|
entity |
| Predicate | chronologicalPositionInNovel |
P10630
|
FINISHED |
| Object | middle section of Breaking Dawn |
—
|
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: middle section of Breaking Dawn | Statement: [Book Two: Jacob, chronologicalPositionInNovel, middle section of Breaking Dawn]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: chronologicalPositionInNovel Context triple: [Book Two: Jacob, chronologicalPositionInNovel, middle section of Breaking Dawn]
-
A.
positionInStory
Indicates the point or role an event, character, or element occupies within the overall sequence or structure of a story.
-
B.
chronologicalPosition
chosen
Indicates the relative ordering of one event or entity in time with respect to another.
-
C.
positionInFiction
Indicates that one entity holds a specific role, status, or placement within a fictional work or narrative.
-
D.
rankWithinChapter
Indicates the relative ordering or position of an item among other items within the same chapter.
-
E.
foundInChapter
Indicates that something (such as a concept, section, or element) is contained within or occurs in a specific chapter.
- 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_69d822e1a2cc81908e5bb93cf61ce3cc |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb4e80aa48190884bab800f357106 |
completed | April 14, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_69de657359c88190b082e3e9f86fc1d7 |
completed | April 14, 2026, 4:04 p.m. |
Created at: April 10, 2026, 1:26 a.m.