Triple
T5111875
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. Henry Dashwood |
E115230
|
entity |
| Predicate | statusAfterEarlyChapters |
P61662
|
FINISHED |
| Object | deceased |
—
|
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: deceased | Statement: [Mr. Henry Dashwood, statusAfterEarlyChapters, deceased]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: statusAfterEarlyChapters Context triple: [Mr. Henry Dashwood, statusAfterEarlyChapters, deceased]
-
A.
chapterAfter
Indicates that one chapter directly follows another in a sequential ordering.
-
B.
isFinalChapterOf
Indicates that one entity is the concluding or last chapter within the sequence of chapters of another entity (typically a work or volume).
-
C.
hadChapterOf
Indicates that an entity (such as a book or document) includes or contains a specific chapter as one of its parts.
-
D.
statusAfterFirstFilm
Indicates the status or condition of an entity immediately following the release or completion of its first film.
-
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. 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_69bd4441d1648190a54a533895041987 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd75ca57e881908242def2a032902e |
completed | March 20, 2026, 4:28 p.m. |
| PD | Predicate disambiguation | batch_69bd715fe3a8819087d3065adddba515 |
completed | March 20, 2026, 4:10 p.m. |
| PDg | Predicate description generation | batch_69bd72e1b7cc8190b2e621fdf8f22e38 |
completed | March 20, 2026, 4:16 p.m. |
Created at: March 20, 2026, 1:41 p.m.