Triple
T2831458
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hussein |
E62246
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Hossayn |
E302311
|
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: Hossayn | Statement: [Hussein, hasVariant, Hossayn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hossayn Context triple: [Hussein, hasVariant, Hossayn]
-
A.
Hussain
Hussain is a common given name and surname of Arabic origin, widely used in Muslim communities around the world.
-
B.
Hossain
chosen
Hossain is a common transliteration variant of the Arabic given name Hussein, widely used in Muslim-majority regions.
-
C.
Hamed
Hamed is a masculine given name commonly used in Arabic-speaking and Muslim-majority cultures.
-
D.
Hamid
Hamid is a common Arabic-origin surname used by various notable individuals across the Muslim world and diaspora.
-
E.
Hussaini
Hussaini is a small, picturesque village in Pakistan’s Hunza Valley, best known for its dramatic mountain scenery and the famous, vertigo-inducing Hussaini suspension bridge.
- 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_69ab4c3c39188190955b9c49d98463d8 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdebd5a2c81908f0e30a0ae0eb8df |
completed | March 7, 2026, 8:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b055d3dbb8819094df5e6751dd96c4 |
completed | March 10, 2026, 5:33 p.m. |
Created at: March 6, 2026, 10:01 p.m.