Triple
T3655090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hamida Banu Begum |
E77508
|
entity |
| Predicate | courtStatus |
P50738
|
FINISHED |
| Object | high-ranking royal consort |
—
|
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: high-ranking royal consort | Statement: [Hamida Banu Begum, courtStatus, high-ranking royal consort]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: courtStatus Context triple: [Hamida Banu Begum, courtStatus, high-ranking royal consort]
-
A.
defendantStatus
Indicates the legal condition or standing of a defendant within a judicial or law-enforcement process.
-
B.
appealStatus
Indicates the current state or outcome of an appeal within a review or decision process.
-
C.
courtContext
Indicates the legal or judicial setting, circumstances, or framework within which a court-related action or relationship takes place.
-
D.
courtOrdered
Indicates that an action, condition, or relationship exists because it has been formally mandated or imposed by a court order.
-
E.
hasStateCourt
Indicates that a given jurisdiction or region possesses an official court that operates at the state level.
- 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.