Triple
T9527375
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shirin |
E229793
|
entity |
| Predicate | alternativeTransliteration |
P5923
|
FINISHED |
| Object | Shereen |
E806211
|
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: Shereen | Statement: [Shirin, alternativeTransliteration, Shereen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shereen Context triple: [Shirin, alternativeTransliteration, Shereen]
-
A.
Shireen
chosen
Shireen is a feminine given name of Persian origin, commonly used in various cultures across the Middle East and South Asia.
-
B.
Samira
Samira is a feminine given name of Arabic origin commonly used across the Middle East, North Africa, and South Asia.
-
C.
Ayesha
Ayesha is a central fictional heroine in Bankim Chandra Chattopadhyay’s historical Bengali novel "Durgeshnandini," known for her beauty, courage, and tragic love.
-
D.
Salma
Salma is a feminine given name of Arabic origin, commonly used in various cultures around the world.
-
E.
Leila
Leila is a tragic female character in Lord Byron’s narrative poem "The Giaour," whose fate embodies themes of forbidden love, betrayal, and vengeance.
- 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_69ca8479934c81908006d0e6e970ae05 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd989c831081908877e42f7ead84ba |
completed | April 1, 2026, 10:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1527253588190ac365203ef382a2d |
completed | April 4, 2026, 6:03 p.m. |
Created at: March 30, 2026, 8 p.m.