Triple
T2071782
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luisa |
E44829
|
entity |
| Predicate | hasDiminutive |
P456
|
FINISHED |
| Object | Luisinha |
E44829
|
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: Luisinha | Statement: [Luisa, hasDiminutive, Luisinha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Luisinha Context triple: [Luisa, hasDiminutive, Luisinha]
-
A.
Luisa
chosen
Luisa is a feminine given name used in various languages, particularly Romance languages, as a form of the name Louise.
-
B.
Margarida
Margarida is a given name, commonly used in Portuguese and Catalan, that corresponds to the English name Margaret.
-
C.
Blanca
Blanca is a feminine given name, common in Spanish-speaking cultures, that corresponds to the English and French name Blanche.
-
D.
Francisca
Francisca is a feminine given name, used in various European and Latin American cultures, that is cognate with the English name Frances.
-
E.
Mariquita
Mariquita is a historic town in central Colombia known as an early colonial settlement and former mining center.
- 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_69a88916c2b48190a5ca2e9b12cad3ed |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abba0d20bc8190b19a32157f8b1607 |
completed | March 7, 2026, 5:39 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae272bd51881909b7da12925195417 |
completed | March 9, 2026, 1:49 a.m. |
Created at: March 4, 2026, 7:41 p.m.