Triple
T17036554
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Last Stop |
E413333
|
entity |
| Predicate | hasChapterStructure |
P125600
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Last Stop, hasChapterStructure, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasChapterStructure Context triple: [Last Stop, hasChapterStructure, yes]
-
A.
containsChapter
Indicates that one entity (typically a larger work or document) includes another entity as a chapter within its structure.
-
B.
hasGeneralChapter
Indicates that an entity is associated with, or contains, a general chapter (a broad or overarching section) within a larger structured document or framework.
-
C.
numberOfChapters
Indicates the total count of chapters associated with a given entity.
-
D.
hasLocalChaptersIn
Indicates that an organization maintains one or more local chapters or branches within a specified geographic area or location.
-
E.
hasChapterFromViewpoint
Indicates that a chapter in a work is narrated or presented from the perspective or viewpoint of a particular entity.
- F. None of above. chosen
Provenance (4 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_69d886cd18288190b006abab23f811b7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d8f26f50819085dfd0fbecd6394d |
completed | April 18, 2026, 7:18 p.m. |
| PD | Predicate disambiguation | batch_69e35d5be7f48190af9db67a1e23850f |
completed | April 18, 2026, 10:30 a.m. |
| PDg | Predicate description generation | batch_69e3753f93c88190808fec5692f66699 |
completed | April 18, 2026, 12:12 p.m. |
Created at: April 10, 2026, 5:33 a.m.