Triple
T3745169
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miriam |
E81192
|
entity |
| Predicate | nameVariant |
P744
|
FINISHED |
| Object | Μαριάμ |
E153359
|
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: Μαριάμ | Statement: [Miriam, nameVariant, Μαριάμ]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Μαριάμ Context triple: [Miriam, nameVariant, Μαριάμ]
-
A.
Maryam
chosen
Maryam is a revered figure in Islam, honored in the Qur’an as the mother of Prophet Isa (Jesus) and a model of piety and devotion.
-
B.
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.
-
C.
Habiba
Habiba is a feminine given name commonly used in Arabic-speaking and Muslim-majority cultures, meaning "beloved" or "darling."
-
D.
Leyla
"Leyla" is a novel by German-Turkish author Feridun Zaimoglu that explores themes of migration, identity, and womanhood through the life story of its titular protagonist.
-
E.
Zohra
Zohra is a character in Naguib Mahfouz’s novel "Miramar," which centers on the lives and conflicts of residents in a pension in Alexandria, Egypt.
- 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_69ad8b19b7b08190a6188804e99c53e9 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcb58c9048190a055d1f4a7e6b699 |
completed | March 8, 2026, 7:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4db2c2c5081909b83d89c989a8d1c |
completed | March 14, 2026, 3:51 a.m. |
Created at: March 8, 2026, 3:35 p.m.