Triple
T19306091
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Helmstedt |
E482831
|
entity |
| Predicate | hasFormerUniversity |
P9419
|
FINISHED |
| Object | University of Helmstedt |
—
|
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: University of Helmstedt | Statement: [Helmstedt, hasFormerUniversity, University of Helmstedt]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFormerUniversity Context triple: [Helmstedt, hasFormerUniversity, University of Helmstedt]
-
A.
hasFormerInstitution
chosen
Indicates that an entity was previously affiliated with, employed by, or enrolled in a particular institution in the past.
-
B.
hasFormerInstitutionName
Indicates that an institution was previously known by a different name.
-
C.
hasUniversities
Indicates that an entity possesses, contains, or is associated with one or more universities.
-
D.
universityFormerName
Indicates that a university previously had a different official name before adopting its current one.
-
E.
firstTaughtAt
Indicates the institution or place where an entity (typically a person) began their teaching career or taught for the first time.
- 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_69d8e8d04d5c8190baa816986f2b1d1e |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e604c84fe08190869463bdd0324160 |
completed | April 20, 2026, 10:49 a.m. |
| PD | Predicate disambiguation | batch_69e4dd0bc7508190a6f9d56bd4c3404f |
completed | April 19, 2026, 1:47 p.m. |
Created at: April 10, 2026, 1:31 p.m.