Triple
T29521448
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Western Michigan Broncos football |
E748945
|
entity |
| Predicate | goesByAbbreviation |
P148953
|
FINISHED |
| Object | WMU |
—
|
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: WMU | Statement: [Western Michigan Broncos football, goesByAbbreviation, WMU]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: goesByAbbreviation Context triple: [Western Michigan Broncos football, goesByAbbreviation, WMU]
-
A.
isAbbreviation
Indicates that one term is a shortened or abbreviated form of another term.
-
B.
usesAbbreviationOf
chosen
Indicates that one entity employs a shortened or abbreviated form of the name or designation of another entity.
-
C.
canBeUsedWithAbbreviation
Indicates that one entity (such as a term, phrase, or expression) is suitable to be used together with a particular abbreviation.
-
D.
correspondsToAbbreviationInGerman
Indicates that one entity is the full form or concept for which the other entity serves as the corresponding abbreviation in the German language.
-
E.
typeOfAbbreviation
Indicates that one term is an abbreviation of a specific type or category (e.g., acronym, initialism) of another expression.
- 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_69f0bd46d99c81908ba9d01cc1dbef7d |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_69f66c9973b08190bbb12bd759f0578e |
completed | May 2, 2026, 9:28 p.m. |
| PD | Predicate disambiguation | batch_69f6633ac8a88190ab0cda62bbfcf9b0 |
completed | May 2, 2026, 8:48 p.m. |
Created at: April 28, 2026, 4:41 p.m.