Triple
T21587427
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mahmood |
E532686
|
entity |
| Predicate | hasVariantSpelling |
P457
|
FINISHED |
| Object | Mehmud |
—
|
NE NERFINISHED |
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: Mehmud | Statement: [Mahmood, hasVariantSpelling, Mehmud]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mehmud Context triple: [Mahmood, hasVariantSpelling, Mehmud]
-
A.
Mahmud
chosen
Mahmud is a masculine given name of Arabic origin commonly used in various Muslim-majority cultures.
-
B.
Mahmud Ahmad
Mahmud Ahmad was a Mahdist general who led Sudanese forces against the Anglo-Egyptian army during the late 19th-century Mahdist War.
-
C.
Mohammad Qasim
Mohammad Qasim was a prominent Persian painter associated with the Isfahan school, known for his refined miniatures and contributions to Safavid-era art.
-
D.
Raza Murad
Raza Murad is an Indian character actor known for his deep voice and frequent portrayals of villains and authoritative figures in Hindi cinema.
-
E.
Mukumtar-ud-Daula
Mukumtar-ud-Daula was a royal prince of the Hyderabad State, known primarily as one of the sons of Mir Osman Ali Khan, the last Nizam of Hyderabad.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c46251648190876f0427cf2d321b |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69eeeb621ab88190a33a943424ffb306 |
completed | April 27, 2026, 4:51 a.m. |
Created at: April 16, 2026, 6:31 p.m.