Triple
T2183929
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lund University |
E49107
|
entity |
| Predicate | hasStrongDiscipline |
P23433
|
FINISHED |
| Object | engineering |
—
|
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: engineering | Statement: [Lund University, hasStrongDiscipline, engineering]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStrongDiscipline Context triple: [Lund University, hasStrongDiscipline, engineering]
-
A.
strongInDiscipline
chosen
Indicates that an entity possesses a high level of strength, skill, or proficiency in a particular discipline or field.
-
B.
supportsDiscipline
Indicates that one entity provides assistance, resources, or endorsement that helps sustain or advance a particular discipline.
-
C.
hasStrongProgramIn
Indicates that an institution or organization offers a particularly high-quality or well-regarded program in a specified field or area.
-
D.
hasClericalDiscipline
Indicates that an entity is subject to, or governed by, a particular set of clerical or religious disciplinary rules or practices.
-
E.
associatedWithDiscipline
Indicates that an entity has a relevant connection or involvement with a particular academic, professional, or thematic discipline.
- 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_69a88aa72d348190a9544bb5b8a4e71d |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abbf9e99f08190892d34485c8f2f25 |
completed | March 7, 2026, 6:03 a.m. |
| PD | Predicate disambiguation | batch_69abbda32d1881909d1fd83a751fb21c |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:45 p.m.