Triple
T20886241
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Richmond (surname) |
E514286
|
entity |
| Predicate | hasSpellingStability |
P53680
|
FINISHED |
| Object | high in modern English records |
—
|
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: high in modern English records | Statement: [Richmond (surname), hasSpellingStability, high in modern English records]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpellingStability Context triple: [Richmond (surname), hasSpellingStability, high in modern English records]
-
A.
spellingStability
chosen
Indicates the degree to which the spelling of a word or term remains consistent over time or across different uses.
-
B.
hasStandardOrthographySince
Indicates that a language or writing system has used a particular standardized orthography starting from a specified point in time.
-
C.
spellingStatus
Indicates the correctness or condition of the spelling of a given text or term.
-
D.
usesFixedSpellingsForCommonSyllables
Indicates that an entity consistently applies predetermined, standard spellings for frequently occurring syllables.
-
E.
spellingStyle
Indicates the particular orthographic convention or system of spelling that is used or preferred in a given 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_69e0b4f733f081908a401c0b7beb0b9f |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6d058d4dc81908398f8c75e30dc77 |
completed | April 21, 2026, 1:18 a.m. |
| PD | Predicate disambiguation | batch_69e5c9a8dc148190b33ff51894e2a8f9 |
completed | April 20, 2026, 6:37 a.m. |
Created at: April 16, 2026, 12:46 p.m.