Triple
T12697852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hussain |
E303381
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Husein |
E303381
|
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: Husein | Statement: [Hussain, hasVariant, Husein]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Husein Context triple: [Hussain, hasVariant, Husein]
-
A.
Huseyn
Huseyn is a given name of Arabic origin, commonly used in various Muslim-majority cultures as a variant of the name Hussein.
-
B.
Hussain
chosen
Hussain is a common given name and surname of Arabic origin, widely used in Muslim communities around the world.
-
C.
Hassan
Hassan is a male given name of Arabic origin commonly used across the Muslim world and beyond.
-
D.
Hassan
Hassan is a city in the Indian state of Karnataka known as a regional hub and gateway to several important historical and religious sites.
-
E.
Hassan
Hassan is a loyal and selfless Hazara boy whose friendship with Amir and the injustices he endures form the emotional core of the film "The Kite Runner."
- 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_69d7bdef90d48190b46b88270e780946 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961ed26588190ae76ff17159e06ec |
completed | April 10, 2026, 8:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f68eafd4f8819083f20d142e9115ae |
completed | May 2, 2026, 11:54 p.m. |
Created at: April 9, 2026, 5:22 p.m.