Triple
T9213630
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jose |
E221185
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Mosty |
E761132
|
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: Mosty | Statement: [Jose, producer, Mosty]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mosty Context triple: [Jose, producer, Mosty]
-
A.
Mosty
chosen
Mosty is a music producer known for working on J Balvin’s album "Vibras," contributing to its distinctive reggaeton and Latin urban sound.
-
B.
Mamer
Mamer is a Luxembourgish singer-songwriter and musician known for blending folk, rock, and alternative influences in his work.
-
C.
Mosta
Mosta is a town in central Malta best known for its impressive Rotunda church, which has one of the largest unsupported domes in the world.
-
D.
Märsta
Märsta is a town in Stockholm County, Sweden, known as a residential and transport hub near Stockholm Arlanda Airport.
-
E.
Tivissa
Tivissa is a historic village in Catalonia, Spain, known for its scenic setting among the mountains of the Ribera d’Ebre region and its well-preserved medieval core.
- 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_69ca83eae42c8190a0ea9e040710a277 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccda06bf80819094c6e74b4b6a31e4 |
completed | April 1, 2026, 8:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d06613daf88190a0128fd53ea1b134 |
completed | April 4, 2026, 1:15 a.m. |
Created at: March 30, 2026, 7:27 p.m.