Triple
T22404294
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Teresa |
E553842
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Teresita |
E553842
|
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: Teresita | Statement: [Teresa, hasVariant, Teresita]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Teresita Context triple: [Teresa, hasVariant, Teresita]
-
A.
Encarnita
Encarnita is the birth name of Puerto Rican singer-songwriter Kany García, known for her Latin pop and ballad music.
-
B.
Ernestina
Ernestina is a feminine given name of Germanic origin, historically borne by European nobility such as Leonor Ernestina von Daun.
-
C.
Teresa
Teresa is the middle name of Tamar Teresa Day Hennessy.
-
D.
Teresa
Teresa is a central figure in Carlos Fuentes’s novel "The Death of Artemio Cruz," representing both a pivotal love interest and a symbol of the social and emotional conflicts surrounding the protagonist.
-
E.
Teresa
chosen
Teresa is a feminine given name commonly used in various cultures, often associated with notable religious and historical figures.
- 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_69e11e4da7048190b4387d422a9a0de5 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f158b6762c8190991fc14c5ca8e609 |
completed | April 29, 2026, 1:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0b2d51846c8190b1450f90c6e79aeb |
completed | May 18, 2026, 3:16 p.m. |
Created at: April 16, 2026, 8:46 p.m.