Triple
T25306318
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Meaning of Marriage |
E634489
|
entity |
| Predicate | includesChapterOn |
P32494
|
FINISHED |
| Object | singleness and its relationship to marriage |
—
|
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: singleness and its relationship to marriage | Statement: [The Meaning of Marriage, includesChapterOn, singleness and its relationship to marriage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesChapterOn Context triple: [The Meaning of Marriage, includesChapterOn, singleness and its relationship to marriage]
-
A.
containsChapter
Indicates that one entity (typically a larger work or document) includes another entity as a chapter within its structure.
-
B.
chapterOn
chosen
Indicates that one entity (typically a chapter) is about, discusses, or focuses on the subject represented by another entity.
-
C.
containsSubchapter
Indicates that one chapter or section includes another, more specific subchapter as a part of its structure.
-
D.
chapterMentioned
Indicates that a specific chapter is referenced or cited within a given context or source.
-
E.
hasChapterStructure
Indicates that one entity is organized into chapters or contains a defined chapter-based structure in relation to 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_69e75a972c6481909bc11710e8d30a6c |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f6f8565134819096aac0175f924a9f |
completed | May 3, 2026, 7:25 a.m. |
| PD | Predicate disambiguation | batch_69f6f65fd1d08190b88e5e68ba268500 |
completed | May 3, 2026, 7:16 a.m. |
Created at: April 21, 2026, 1:25 p.m.