Triple
T18588602
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vault 687 |
E454300
|
entity |
| Predicate | visitedInChapter |
P36548
|
FINISHED |
| Object | Chapter 5 "Diagon Alley" |
—
|
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: Chapter 5 "Diagon Alley" | Statement: [Vault 687, visitedInChapter, Chapter 5 "Diagon Alley"]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: visitedInChapter Context triple: [Vault 687, visitedInChapter, Chapter 5 "Diagon Alley"]
-
A.
hasChapterFromViewpoint
Indicates that a chapter in a work is narrated or presented from the perspective or viewpoint of a particular entity.
-
B.
visitedBy
Indicates that a location or entity is the destination or target of a visit performed by another entity.
-
C.
foundInChapter
chosen
Indicates that something (such as a concept, section, or element) is contained within or occurs in a specific chapter.
-
D.
hadChapterOf
Indicates that an entity (such as a book or document) includes or contains a specific chapter as one of its parts.
-
E.
containsChapter
Indicates that one entity (typically a larger work or document) includes another entity as a chapter within its structure.
- 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_69d8d38ae7e081908a98df1251842402 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e545b3e564819088e60fc25d1976f0 |
completed | April 19, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69e478c98d4c81909d37a0e72c6e7bd0 |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 11:44 a.m.