Triple
T16699939
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Université de Lorraine |
E405817
|
entity |
| Predicate | hasMetzCampusFunction |
P2465
|
FINISHED |
| Object | teaching |
—
|
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: teaching | Statement: [Université de Lorraine, hasMetzCampusFunction, teaching]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMetzCampusFunction Context triple: [Université de Lorraine, hasMetzCampusFunction, teaching]
-
A.
hasCampusFeature
chosen
Indicates that a campus possesses or includes a specific physical or functional feature.
-
B.
hasCampusCity
Indicates that an educational institution or campus is located in a particular city.
-
C.
hasSurfaceCampus
Indicates that one entity (typically an institution) maintains a physical campus or site located on the surface of another entity (such as a planet or celestial body).
-
D.
hasCampusOn
Indicates that an institution or organization maintains a campus located on a specified geographic area or site.
-
E.
isCampusOfProject
Indicates that a particular campus serves as the location or host site for a given project.
- 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_69d8838db21081909589220fd71440a4 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e383300d108190911e3cba8e07f2dd |
completed | April 18, 2026, 1:12 p.m. |
| PD | Predicate disambiguation | batch_69e319bc73908190a0e38bc926b31f10 |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:19 a.m.