Triple
T7627846
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mir Ali Murad Khan Talpur |
E172681
|
entity |
| Predicate | title |
P38
|
FINISHED |
| Object | Mir |
E160204
|
NE 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: Mir | Statement: [Mir Ali Murad Khan Talpur, title, Mir]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mir Context triple: [Mir Ali Murad Khan Talpur, title, Mir]
-
A.
Mir
Mir was a Soviet and later Russian modular space station that served as a long-term research outpost in low Earth orbit from 1986 to 2001.
-
B.
Mir
chosen
Mir is a traditional South Asian noble title historically used by rulers and aristocrats, particularly in regions such as Sindh under dynasties like the Talpurs.
-
C.
Mir
Mir is a historic town in present-day Belarus, known for its multicultural heritage and the UNESCO-listed Mir Castle Complex.
-
D.
Mari
Mari is a Uralic language spoken by the Mari people, primarily in the Mari El Republic of Russia.
-
E.
Mari
Mari is a character in Paulo Coelho's novel "Veronika Decides to Die," portrayed as a fellow patient in the mental institution who struggles with anxiety and societal expectations.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c699517e348190bd3348b6889200f2 |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6fa831f508190ab2f72326cdf4497 |
completed | March 27, 2026, 9:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c870aa0b048190afe78ce262834f22 |
completed | March 29, 2026, 12:22 a.m. |
Created at: March 27, 2026, 3:56 p.m.