Triple
T1781798
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Silas Phelps |
E39305
|
entity |
| Predicate | appearsInChapterOf |
P795
|
FINISHED |
| Object | later chapters of Adventures of Huckleberry Finn |
—
|
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: later chapters of Adventures of Huckleberry Finn | Statement: [Silas Phelps, appearsInChapterOf, later chapters of Adventures of Huckleberry Finn]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appearsInChapterOf Context triple: [Silas Phelps, appearsInChapterOf, later chapters of Adventures of Huckleberry Finn]
-
A.
containsChapter
Indicates that one entity (typically a larger work or document) includes another entity as a chapter within its structure.
-
B.
appearsIn
chosen
Indicates that an entity is present, featured, or occurs within a particular context, work, or medium.
-
C.
chapterNumber
Indicates the specific ordinal position a chapter occupies within a larger ordered work, such as a book or document.
-
D.
appearsInSeries
Indicates that an entity is featured or occurs within a particular series.
-
E.
chapterInvoked
Indicates that one chapter is formally brought into effect, referenced, or applied within a particular legal, procedural, or narrative context.
- 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_69a88630519c8190a17addd83c4a3ef4 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab74dc9d1481908084ef07872a71f8 |
completed | March 7, 2026, 12:44 a.m. |
| PD | Predicate disambiguation | batch_69aa61cf3ca881908641fd73ce2f7c9d |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:31 p.m.