Triple
T9698926
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lela |
E234723
|
entity |
| Predicate | isRelatedName |
P3889
|
FINISHED |
| Object | Leila |
E110174
|
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: Leila | Statement: [Lela, isRelatedName, Leila]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Leila Context triple: [Lela, isRelatedName, Leila]
-
A.
Leila
chosen
Leila is a tragic female character in Lord Byron’s narrative poem "The Giaour," whose fate embodies themes of forbidden love, betrayal, and vengeance.
-
B.
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.
-
C.
Dalila
Dalila is a biblical figure, often depicted as a Philistine woman who betrays Samson by discovering and revealing the secret of his strength.
-
D.
Suhaila
Suhaila is the young girl protagonist of the children's book "Ladder to the Moon," who embarks on a magical, intergenerational journey with her grandmother to explore themes of compassion and connection.
-
E.
Zeina
Zeina is a feminine given name commonly used in Arabic-speaking and Middle Eastern cultures, often associated with beauty and grace.
- 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_69ca84cb580c8190a7e5f4b3bcdaf2a4 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9d3d425c8190b652d84186b5ce9f |
completed | April 1, 2026, 10:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1af8990608190a841c1fbdb22eb71 |
completed | April 5, 2026, 12:40 a.m. |
Created at: March 30, 2026, 8:18 p.m.