Triple
T9406941
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parkar |
E226609
|
entity |
| Predicate | canBeAnglicizedFormOf |
P30815
|
FINISHED |
| Object | non-English surnames |
—
|
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: non-English surnames | Statement: [Parkar, canBeAnglicizedFormOf, non-English surnames]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canBeAnglicizedFormOf Context triple: [Parkar, canBeAnglicizedFormOf, non-English surnames]
-
A.
isOftenAmericanizedFormOf
chosen
Indicates that one term is a version of another term that has been adapted into common American usage, typically in spelling, form, or style.
-
B.
isGivenNameFormOf
Indicates that one name is a given-name variant or form derived from another name.
-
C.
hasEnglishName
Indicates that an entity is associated with a name expressed in the English language.
-
D.
isRealFormOf
Indicates that one entity is the actual, physically existing or fully realized version of another entity, which may be abstract, conceptual, or a representation.
-
E.
hasTwoWordForm
Indicates that an entity is represented or expressed using a form consisting of exactly two words.
- 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_69ca843280488190bc65600e843ef9e6 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd51c3fc988190ac34cc9e09f8ebfc |
completed | April 1, 2026, 5:11 p.m. |
| PD | Predicate disambiguation | batch_69cca54c37f88190bddccf28e5fe5c84 |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:47 p.m.