Triple
T5809964
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Graduate School of Law |
E128843
|
entity |
| Predicate | mayOfferSpecialization |
P466
|
FINISHED |
| Object | international law |
—
|
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: international law | Statement: [Graduate School of Law, mayOfferSpecialization, international law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mayOfferSpecialization Context triple: [Graduate School of Law, mayOfferSpecialization, international law]
-
A.
hasSpecialist
Indicates that one entity is associated with or assigned to a specialist entity that provides expert support, service, or oversight for it.
-
B.
hasSpecial
Indicates that an entity possesses or is associated with a distinctive or exceptional attribute, status, or feature compared to others.
-
C.
hasSpecialty
chosen
Indicates that an entity possesses a particular area of expertise, focus, or professional specialization.
-
D.
mayServe
Indicates that one entity is permitted or authorized to provide a service or function to another entity.
-
E.
wouldProvide
Indicates that one entity is willing or expected to supply or furnish something to another entity under certain conditions.
- 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_69c0084788848190bcf71f6bc5d71597 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02b52663c8190ab44258468d4296d |
completed | March 22, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69c021d5ecd081908a62dd66e26f8598 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:52 p.m.