Triple
T2282503
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chrysothemis |
E51311
|
entity |
| Predicate | sibling |
P363
|
FINISHED |
| Object | Lipara |
E52777
|
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: Lipara | Statement: [Chrysothemis, sibling, Lipara]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lipara Context triple: [Chrysothemis, sibling, Lipara]
-
A.
Lipara
chosen
Lipara is one of the Hesperides, the nymphs of Greek mythology associated with the evening and the golden apples of the gods.
-
B.
Jandali
Jandali is an Arabic family name most notably associated with Abdulfattah Jandali, the biological father of Apple co-founder Steve Jobs.
-
C.
Liluah
Liluah is a suburban locality in the Howrah district of West Bengal, India, known for its residential areas and railway facilities near Kolkata.
-
D.
Marangona
Marangona is the largest and most famous bell of St Mark's Campanile in Venice, traditionally used to mark the beginning and end of the working day and to signal important civic events.
-
E.
Jopara
Jopara is a mixed language spoken in Paraguay that blends Guaraní and Spanish in everyday communication.
- 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_69a88b08e4308190bdac9aebcca1c91a |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abc21d6d748190980128c1bc5b9621 |
completed | March 7, 2026, 6:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae71e7b44c8190ab647646352b71b7 |
completed | March 9, 2026, 7:08 a.m. |
Created at: March 4, 2026, 7:48 p.m.