Triple
T16562156
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Faculty of Law and Political Sciences of Tunis |
E402364
|
entity |
| Predicate | producedAlumniIn |
P89630
|
FINISHED |
| Object | judiciary |
—
|
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: judiciary | Statement: [Faculty of Law and Political Sciences of Tunis, producedAlumniIn, judiciary]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: producedAlumniIn Context triple: [Faculty of Law and Political Sciences of Tunis, producedAlumniIn, judiciary]
-
A.
alumniOfProgram
Indicates that a person previously completed or participated in a specific educational or training program.
-
B.
workProducedBy
Indicates that a particular work (such as a creation, product, or result) was created, generated, or authored by a specific agent or entity.
-
C.
hasProfessionalAlumni
chosen
Indicates that an institution or organization has alumni who have gone on to work in a specified profession or professional field.
-
D.
namedAfterAlumnusOf
Indicates that one entity is named in honor of a person who is an alumnus of another specified institution or organization.
-
E.
hasNotableAlumniType
Indicates that an entity has notable alumni belonging to a specified category or type.
- 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_69d8838648088190acf97ef11fc3f61b |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3576eb63081908cb5dc6c0a8a13ac |
completed | April 18, 2026, 10:05 a.m. |
| PD | Predicate disambiguation | batch_69e296a47b7481909d9958158510c806 |
completed | April 17, 2026, 8:23 p.m. |
Created at: April 10, 2026, 5:15 a.m.