Triple
T21108418
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sassi |
E520111
|
entity |
| Predicate | comparedTo |
P278
|
FINISHED |
| Object | Laila |
—
|
NE NERFINISHED |
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: Laila | Statement: [Sassi, comparedTo, Laila]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laila Context triple: [Sassi, comparedTo, Laila]
-
A.
Laila
chosen
Laila is a feminine given name used in various cultures, often associated with meanings like "night" or "dark beauty."
-
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.
Leila
Leila is a 1997 Iranian drama film directed by Dariush Mehrjui that explores the emotional and social pressures surrounding infertility and polygamy in contemporary Tehran.
-
D.
Ayesha
Ayesha is the golden-skinned, genetically engineered High Priestess of the Sovereign race and a primary antagonist in Marvel’s Guardians of the Galaxy Vol. 2.
-
E.
Ayesha
Ayesha is a central fictional heroine in Bankim Chandra Chattopadhyay’s historical Bengali novel "Durgeshnandini," known for her beauty, courage, and tragic love.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b509a318819092fbbcb21d1fe603 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e720ffa998819082db225363ac3b23 |
completed | April 21, 2026, 7:02 a.m. |
Created at: April 16, 2026, 2:54 p.m.