Triple
T22203197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Messiah University |
E548732
|
entity |
| Predicate | changedNameToUniversity |
P49743
|
FINISHED |
| Object | 2020 |
—
|
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: 2020 | Statement: [Messiah University, changedNameToUniversity, 2020]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: changedNameToUniversity Context triple: [Messiah University, changedNameToUniversity, 2020]
-
A.
universityRenamedWith
chosen
Indicates that a university has changed its name to a new one, linking the original institution to its updated name.
-
B.
universityFormerName
Indicates that a university previously had a different official name before adopting its current one.
-
C.
formerUniversityName
Indicates that an institution previously had a different official university name than the one it currently holds.
-
D.
renamedAsKarlMarxUniversity
Indicates that an entity was renamed to "Karl Marx University" at some point in time.
-
E.
universityName
Indicates the official name associated with a particular university.
- 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_69e11e3ecc7c8190b5f94cd8f42e9d37 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12b25eac4819094b3c50027ed66db |
completed | April 28, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69e71b4dcc408190a30429fb08fcf39e |
completed | April 21, 2026, 6:38 a.m. |
Created at: April 16, 2026, 8:36 p.m.