Triple
T14476228
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carmen |
E358979
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Carmela |
E844361
|
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: Carmela | Statement: [Carmen, hasVariant, Carmela]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carmela Context triple: [Carmen, hasVariant, Carmela]
-
A.
Carmela
chosen
Carmela is a feminine given name of Latin origin, commonly used in Spanish- and Italian-speaking countries and often associated with religious and cultural traditions.
-
B.
Rosita
Rosita is a shy but talented pig and devoted mother who becomes a standout performer in the animated musical film "Sing."
-
C.
Rosita
Rosita is a bilingual, turquoise monster Muppet on Sesame Street known for introducing Spanish language and Latino culture to the show.
-
D.
Carmen Vasquez
Carmen Vasquez is a supporting character in the 2000 crime-action film "Shaft," involved in the investigation led by detective John Shaft.
-
E.
Carmela Zumbado
Carmela Zumbado is an American actress known for her roles in television series such as You and Power Book IV: Force, as well as various film and TV projects.
- 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_69d827966698819082e140837737501d |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de91fc1fc48190842b09aa03ba79f8 |
completed | April 14, 2026, 7:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd64a0553081909fd88d8f39ed1a01 |
completed | May 8, 2026, 4:20 a.m. |
Created at: April 10, 2026, 1:20 a.m.