Triple
T887810
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kings |
E19168
|
entity |
| Predicate | mentionsFigure |
P831
|
FINISHED |
| Object | Jezebel |
E32489
|
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: Jezebel | Statement: [Kings, mentionsFigure, Jezebel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jezebel Context triple: [Kings, mentionsFigure, Jezebel]
-
A.
Jezebel
chosen
Jezebel is a feminist-leaning online magazine and blog known for its sharp commentary on gender, culture, and media.
-
B.
Maria Magdalena Keverich
Maria Magdalena Keverich was a German woman best known as the mother of the composer Ludwig van Beethoven.
-
C.
Ofelia
Ofelia is the imaginative young girl in Guillermo del Toro’s dark fantasy film "Pan’s Labyrinth," whose encounters with mythical creatures mirror the brutal realities of post–Civil War Spain.
-
D.
Caterina
Caterina is an Italian given name, equivalent to Catherine, commonly used for women in Italian-speaking and related cultures.
-
E.
Diana
Diana is a feminine given name of Latin origin, famously borne by the Roman goddess of the hunt and by Diana, Princess of Wales.
- 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_69a4939c32488190a7ccd41cf0abb22b |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b2b8063081909566c404ca63a29e |
completed | March 1, 2026, 9:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7c021732c8190a3b4020f8e3cb90e |
completed | March 4, 2026, 5:16 a.m. |
Created at: March 1, 2026, 7:39 p.m.