Triple
T36235264
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MacEwan |
E891359
|
entity |
| Predicate | hasTypicalSpellingPrefix |
P56633
|
FINISHED |
| Object | Mac |
—
|
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: Mac | Statement: [MacEwan, hasTypicalSpellingPrefix, Mac]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalSpellingPrefix Context triple: [MacEwan, hasTypicalSpellingPrefix, Mac]
-
A.
hasTypicalSpelling
chosen
Indicates that one form is the standard or commonly accepted spelling of another form.
-
B.
hasPrepositionalPrefix
Indicates that one entity functions as a prepositional prefix attached to or modifying another entity.
-
C.
hasPrefixMeaning
Indicates that one entity serves as a semantic prefix of another, contributing a specific meaning to the start of the second entity.
-
D.
hasAbbreviationPrefix
Indicates that one term’s abbreviation begins with the same initial sequence of characters as another specified string or term.
-
E.
hasSurnamePrefix
Indicates that one entity’s surname begins with, or is prefixed by, the string or component specified by the other 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_69f76e4387048190a1b27bcbf4ec7423 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69ff965f9be48190b015b788207be676 |
completed | May 9, 2026, 8:17 p.m. |
| PD | Predicate disambiguation | batch_69ff95d3015c8190b9d293fe31b859c3 |
completed | May 9, 2026, 8:15 p.m. |
Created at: May 3, 2026, 4:09 p.m.