Triple
T30208365
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Castle Dracula |
E767999
|
entity |
| Predicate | firstVisitorInNovel |
P203636
|
FINISHED |
| Object | Jonathan Harker |
E261891
|
NE 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: Jonathan Harker | Statement: [Castle Dracula, firstVisitorInNovel, Jonathan Harker]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstVisitorInNovel Context triple: [Castle Dracula, firstVisitorInNovel, Jonathan Harker]
-
A.
firstAppearanceBook
Indicates the book in which an entity (such as a character or concept) is first introduced or appears.
-
B.
isFirstCompletedNovelBy
Indicates that the object is the first novel ever completed by the subject.
-
C.
firstAppearanceChapter
Indicates the chapter in which an entity (such as a character, item, or concept) is first introduced or appears in a work.
-
D.
hasProtagonistInFirstVolume
Indicates that a work’s first volume features a specific entity as its main character.
-
E.
firstAppearanceStory
Indicates the story in which an entity is depicted or mentioned for the first time.
- F. None of above. chosen
Provenance (5 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_69f2247eb0848190b4032f302d39c0d9 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_6a01bb06422c819095bb42f6f3a0e801 |
completed | May 11, 2026, 11:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a2758a90ec88190848bb2ed84476a2e |
completed | June 9, 2026, 12:04 a.m. |
| PD | Predicate disambiguation | batch_6a01b9991c348190ac49b65ea2fd86ed |
completed | May 11, 2026, 11:12 a.m. |
| PDg | Predicate description generation | batch_6a01bb0584608190a27ad07f095ea7fd |
completed | May 11, 2026, 11:18 a.m. |
Created at: April 29, 2026, 7:32 p.m.