Triple
T36056634
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr Connétable |
E1042963
|
entity |
| Predicate | correspondsToEnglish |
P126165
|
FINISHED |
| Object | Mr Constable |
—
|
NE NERFINISHED |
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: Mr Constable | Statement: [Mr Connétable, correspondsToEnglish, Mr Constable]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: correspondsToEnglish Context triple: [Mr Connétable, correspondsToEnglish, Mr Constable]
-
A.
correspondsToEnglishSpelling
chosen
Indicates that one representation, form, or transcription matches or is equivalent to the standard English spelling of the same item.
-
B.
correspondsToEnglishLetter
Indicates that one entity is the English alphabet letter that matches, represents, or is equivalent to the other entity.
-
C.
equivalentEnglishForm
Indicates that two expressions share the same meaning in English, serving as equivalent linguistic forms.
-
D.
correspondsToLatinWord
Indicates that one element is the equivalent or matching term of another element in Latin.
-
E.
correspondsToInArabic
Indicates that one entity is the equivalent or matching counterpart of another entity specifically in the Arabic language.
- 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_69f76e2f09448190b0486d5ecad5e243 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7c29e1b848190b945c6c6120a5330 |
completed | May 3, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69f7c1b6e7a881908deb96bedb2713f4 |
completed | May 3, 2026, 9:44 p.m. |
Created at: May 3, 2026, 4:08 p.m.