Triple
T3655089
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hamida Banu Begum |
E77508
|
entity |
| Predicate | roleInAkbarsLife |
P50737
|
FINISHED |
| Object | advisor and respected elder |
—
|
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: advisor and respected elder | Statement: [Hamida Banu Begum, roleInAkbarsLife, advisor and respected elder]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInAkbarsLife Context triple: [Hamida Banu Begum, roleInAkbarsLife, advisor and respected elder]
-
A.
relationToNurJahan
Indicates a relationship or connection that an entity has specifically to Nur Jahan.
-
B.
roleInMonarchyPeriod
Indicates that an entity held a specific role or position during a defined period of a monarchy.
-
C.
wasPuppetRulerOf
Indicates that one entity served as a ruler of another entity while being controlled or heavily influenced by a separate, more powerful authority.
-
D.
PersianCommander
Indicates that an entity serves as a military commander for, or in the context of, the Persian forces or Persian polity.
-
E.
MamlukCommander
Indicates that an entity serves as a military commander within the Mamluk political or military structure in relation to another entity or context.
- 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_69ad85def5cc8190863dccf55a18bebb |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc3baf57c8190b72b5d1b910d9db6 |
completed | March 8, 2026, 6:45 p.m. |
| PD | Predicate disambiguation | batch_69adb84650148190bf79231105e58d7f |
completed | March 8, 2026, 5:56 p.m. |
| PDg | Predicate description generation | batch_69adbae14d488190a6024548979c6faf |
completed | March 8, 2026, 6:07 p.m. |
Created at: March 8, 2026, 3:24 p.m.