Triple
T2148513
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bantia |
E47124
|
entity |
| Predicate | hasSubjectOfStudy |
P36625
|
FINISHED |
| Object | ancient 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: ancient law | Statement: [Bantia, hasSubjectOfStudy, ancient law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSubjectOfStudy Context triple: [Bantia, hasSubjectOfStudy, ancient law]
-
A.
studiedBy
Indicates that a subject (such as a field, topic, or object) is examined, researched, or learned by an agent (such as a person or group).
-
B.
hasLanguageOfStudy
Indicates that an entity studies or is engaged in learning a particular language.
-
C.
studiedUnder
Indicates that one entity received instruction, training, or mentorship from another, typically in an academic or apprenticeship context.
-
D.
partOfStudy
Indicates that something is a component, segment, or subset within a larger study or research project.
-
E.
usesResearchSubject
Indicates that one entity employs or utilizes another entity as a research subject in a study or investigation.
- F. None of above. chosen
Provenance (4 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_69a88a1933e0819094f18426ed74180f |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abbeaa14bc81908486683decd7ae42 |
completed | March 7, 2026, 5:59 a.m. |
| PD | Predicate disambiguation | batch_69abbd9846e88190b6c2941dd9ce7749 |
completed | March 7, 2026, 5:54 a.m. |
| PDg | Predicate description generation | batch_69abbea8bd4881908f72019a5acf6174 |
completed | March 7, 2026, 5:59 a.m. |
Created at: March 4, 2026, 7:44 p.m.