Triple
T115154
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mughal Empire |
E2322
|
entity |
| Predicate | courtLanguage |
P6495
|
FINISHED |
| Object | Persian |
—
|
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: Persian | Statement: [Mughal Empire, courtLanguage, Persian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: courtLanguage Context triple: [Mughal Empire, courtLanguage, Persian]
-
A.
judicialBody
Indicates that an entity serves as a court or tribunal with authority to adjudicate legal disputes or interpret and apply the law.
-
B.
judicialCircuit
Indicates the judicial circuit within which a legal entity, case, or jurisdiction is organized or falls under authority.
-
C.
legalSystem
Indicates the formal framework of laws, rules, and institutions that governs how legal matters are defined, interpreted, and enforced within a society or jurisdiction.
-
D.
typeOfJurisdiction
Indicates the specific kind or category of legal authority or control that one jurisdiction holds in relation to a given legal or administrative context.
-
E.
legalDoctrine
Indicates that one legal principle, rule, or theory is being applied, referenced, or relied upon as an authoritative basis for interpreting or deciding a legal issue.
- 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_69a2506c5428819085c28a8884790e29 |
completed | Feb. 28, 2026, 2:18 a.m. |
| NER | Named-entity recognition | batch_69a25760af348190bf402089c240887d |
completed | Feb. 28, 2026, 2:48 a.m. |
| PD | Predicate disambiguation | batch_69a2564417848190a8a8a38e97348963 |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a2575d8a648190ad8e10d4b04e5e07 |
completed | Feb. 28, 2026, 2:47 a.m. |
Created at: Feb. 28, 2026, 2:24 a.m.