Triple
T16479206
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M’Zab Valley |
E400270
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Melika |
E400265
|
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: Melika | Statement: [M’Zab Valley, hasPart, Melika]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Melika Context triple: [M’Zab Valley, hasPart, Melika]
-
A.
Melika
chosen
Melika is a historic oasis town in Algeria’s M’zab Valley, known for its traditional Ibadi Muslim community and distinctive Saharan architecture.
-
B.
Metlika
Metlika is a historic town in southeastern Slovenia known for its wine-making tradition and cultural heritage in the Bela Krajina region.
-
C.
Mella
Mella is a Spanish-language surname most notably associated with Cuban revolutionary leader Julio Antonio Mella.
-
D.
Milina
Milina is a seaside village in the Pelion region of central Greece, known for its tranquil beaches and views across the Pagasetic Gulf.
-
E.
Maleka
Maleka is a feminine given name, typically considered a variant spelling of Malika and used in various cultures.
- 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_69d883813098819084f5409539723b59 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e01230881908b2147a25f78b7f4 |
completed | April 18, 2026, 7:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a004f60ea8881908f073a28c407a1f4 |
completed | May 10, 2026, 9:26 a.m. |
Created at: April 10, 2026, 5:13 a.m.