Triple
T12392539
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harry Potter audiobook narration (UK) |
E296031
|
entity |
| Predicate | hasAccents |
P14722
|
FINISHED |
| Object | various British accents |
—
|
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: various British accents | Statement: [Harry Potter audiobook narration (UK), hasAccents, various British accents]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAccents Context triple: [Harry Potter audiobook narration (UK), hasAccents, various British accents]
-
A.
hasAccent
chosen
Indicates that an entity speaks with or possesses a particular accent or distinctive pronunciation style.
-
B.
hasAccentPosition
Indicates the position within a word or phrase where the primary accent or stress is placed.
-
C.
usesDiacritics
Indicates that the referenced text or linguistic element employs diacritical marks as part of its written form.
-
D.
hasUnicode
Indicates that an entity is associated with, represented by, or encoded using a specific Unicode character or sequence.
-
E.
usesDiacriticsFrom
Indicates that one entity employs or incorporates the diacritical marks that originate from or are characteristic of another entity.
- 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_69d6ad9e653c8190b1473c860ee53dae |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d93fd228488190b216abd1c341563c |
completed | April 10, 2026, 6:22 p.m. |
| PD | Predicate disambiguation | batch_69d93ed256788190b704cad171a4824e |
completed | April 10, 2026, 6:17 p.m. |
Created at: April 8, 2026, 9:54 p.m.