Triple
T15608788
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harold Crick |
E375231
|
entity |
| Predicate | fateInOriginalDraft |
P110514
|
FINISHED |
| Object | intended to die at the end of the novel |
—
|
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: intended to die at the end of the novel | Statement: [Harold Crick, fateInOriginalDraft, intended to die at the end of the novel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fateInOriginalDraft Context triple: [Harold Crick, fateInOriginalDraft, intended to die at the end of the novel]
-
A.
fate
Indicates that an entity is destined or predetermined to experience a particular outcome or course of events beyond its control.
-
B.
fateInFactory
Indicates that an entity meets its end, outcome, or final disposition within a factory setting.
-
C.
fateInWork
Indicates that an entity’s fate, outcome, or destiny is determined, depicted, or significantly influenced within a particular work (such as a book, film, or other creative piece).
-
D.
fateInLegend
Indicates the ultimate outcome or destiny attributed to an entity within a particular legend or mythic narrative.
-
E.
fateInBooks
chosen
Indicates that a character’s destiny, outcome, or predetermined path is described or revealed within written works or books.
- 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_69d85ccf2794819096cda4cbcb02d478 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e8024948190a6c711f2e5c2aac4 |
completed | April 16, 2026, 2:50 a.m. |
| PD | Predicate disambiguation | batch_69deda844af081909e658ebc9d9b403d |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:13 a.m.