Triple
T5476283
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Flour City |
E122961
|
entity |
| Predicate | hasSpellingNote |
P457
|
FINISHED |
| Object | often confused with "Flower City" |
—
|
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: often confused with "Flower City" | Statement: [The Flour City, hasSpellingNote, often confused with "Flower City"]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpellingNote Context triple: [The Flour City, hasSpellingNote, often confused with "Flower City"]
-
A.
hasTypicalSpelling
Indicates that one form is the standard or commonly accepted spelling of another form.
-
B.
hasVariantSpelling
chosen
Indicates that one term is an alternative spelling form of another term.
-
C.
effectOnSpelling
Indicates a relationship where one factor influences or alters the way something is spelled.
-
D.
hasPronunciationDifferenceFrom
Indicates that two linguistic items differ in how they are pronounced.
-
E.
sharesSpellingWith
Indicates that two entities have identical or substantially identical written forms (i.e., they are spelled the same way).
- 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_69bd46459ff48190823377457bcf7128 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd923639bc81909a83dd4fcaa8c636 |
completed | March 20, 2026, 6:30 p.m. |
| PD | Predicate disambiguation | batch_69bd91a58c448190904964a439045e05 |
completed | March 20, 2026, 6:27 p.m. |
Created at: March 20, 2026, 2:09 p.m.