Triple
T12459309
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hany Mukhtar |
E297746
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Hany |
E833691
|
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: Hany | Statement: [Hany Mukhtar, givenName, Hany]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hany Context triple: [Hany Mukhtar, givenName, Hany]
-
A.
Hany
chosen
Hany is a masculine given name commonly used in Arabic-speaking cultures.
-
B.
Hani
The Hani are an ethnic minority group in China, primarily known for their terraced rice farming, distinctive traditional dress, and rich folk culture in the mountainous regions of Yunnan.
-
C.
Hannya
Hannya is the enigmatic, mask-wearing antagonist in Ghostwire: Tokyo, leading a mysterious cult and orchestrating the mass disappearance of the city's population.
-
D.
Haya
Haya is a feminine given name of Arabic origin, commonly used in the Middle East and among Arabic-speaking communities.
-
E.
Haya
The Haya are a Bantu-speaking ethnic group of northwestern Tanzania, known for their advanced precolonial ironworking and intensive banana-based agriculture around Lake Victoria.
- 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_69d6ada270808190b1a2b2e7b02bb426 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94da46a588190bc888fafd6d1eb5d |
completed | April 10, 2026, 7:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f63f1b0a3081909cf22970586755e9 |
completed | May 2, 2026, 6:14 p.m. |
Created at: April 8, 2026, 9:56 p.m.