Triple
T20769474
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hugo Granger-Weasley |
E511185
|
entity |
| Predicate | firstAppearanceSection |
P42626
|
FINISHED |
| Object | Epilogue: Nineteen Years Later |
—
|
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: Epilogue: Nineteen Years Later | Statement: [Hugo Granger-Weasley, firstAppearanceSection, Epilogue: Nineteen Years Later]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstAppearanceSection Context triple: [Hugo Granger-Weasley, firstAppearanceSection, Epilogue: Nineteen Years Later]
-
A.
firstAppearancePart
Indicates that an entity makes its first appearance as a component or segment within a larger work or sequence.
-
B.
firstAppearanceFor
Indicates that an entity marks the initial occurrence or debut of another entity within a given context or medium.
-
C.
firstAppearanceAct
Indicates the act in which an entity makes its first appearance within a work or performance.
-
D.
firstAppearanceChapter
chosen
Indicates the chapter in which an entity (such as a character, item, or concept) is first introduced or appears in a work.
-
E.
firstAppearanceApprox
Indicates that one entity is the approximate or estimated first appearance of another entity in time or context.
- 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_69e0b4ca01148190ac018e57e0cab46f |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c265f7dc8190a084e35d38d2783a |
completed | April 21, 2026, 12:18 a.m. |
| PD | Predicate disambiguation | batch_69e5c0550ec481908a0877fb2409d983 |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 12:36 p.m.