Triple
T27461638
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FitzCharles |
E692761
|
entity |
| Predicate | spellingVariantPattern |
P162658
|
FINISHED |
| Object | Fitz- + male given name |
—
|
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: Fitz- + male given name | Statement: [FitzCharles, spellingVariantPattern, Fitz- + male given name]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spellingVariantPattern Context triple: [FitzCharles, spellingVariantPattern, Fitz- + male given name]
-
A.
hasVariantSpelling
Indicates that one term is an alternative spelling form of another term.
-
B.
spellingStyle
Indicates the particular orthographic convention or system of spelling that is used or preferred in a given context.
-
C.
linguisticVariant
Indicates that one linguistic form is an alternative version or expression of another within the same or closely related language context.
-
D.
languageVariant
Indicates that one language is a variant, dialect, or localized form of another language.
-
E.
correspondsToEnglishSpelling
Indicates that one representation, form, or transcription matches or is equivalent to the standard English spelling of the same item.
- 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_69ef5207903881909427745cda05d27a |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69f62dfa4f3881908a45c137df7fa0db |
completed | May 2, 2026, 5:01 p.m. |
| PD | Predicate disambiguation | batch_69f62c1762f881908c25e8f70ecd5041 |
completed | May 2, 2026, 4:53 p.m. |
| PDg | Predicate description generation | batch_69f62cd1912c8190ab3f3288442115a4 |
completed | May 2, 2026, 4:56 p.m. |
Created at: April 27, 2026, 12:50 p.m.