Triple
T20093858
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matías Ramón Mella |
E496345
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Mella |
E115682
|
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: Mella | Statement: [Matías Ramón Mella, familyName, Mella]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mella Context triple: [Matías Ramón Mella, familyName, Mella]
-
A.
Mella
chosen
Mella is a Spanish-language surname most notably associated with Cuban revolutionary leader Julio Antonio Mella.
-
B.
Mella
Mella is a river in northern Italy that flows through the province of Brescia before joining the Oglio River.
-
C.
Meziella
Meziella is a small, lesser-known genus of flowering plants within the water milfoil family Haloragaceae.
-
D.
Melsisi
Melsisi is a coastal village and mission station on Pentecost Island in Vanuatu, known for its Catholic mission, school, and local health services.
-
E.
Melika
Melika is a historic oasis town in Algeria’s M’zab Valley, known for its traditional Ibadi Muslim community and distinctive Saharan architecture.
- 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_69da626eee3881909f3454986d4a6511 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6666a7a94819080ebabfba9762f97 |
completed | April 20, 2026, 5:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a082707c7908190a3889541ea8a650b |
completed | May 16, 2026, 8:12 a.m. |
Created at: April 11, 2026, 11:23 p.m.