Triple
T3368870
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elisa |
E70903
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Elisa (Spanish form) |
E70903
|
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: Elisa (Spanish form) | Statement: [Elisa, hasVariant, Elisa (Spanish form)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Elisa (Spanish form) Context triple: [Elisa, hasVariant, Elisa (Spanish form)]
-
A.
Elisa
chosen
Elisa is a feminine given name of Hebrew origin, often considered a short form of Elisabeth and used in various languages including Italian, Spanish, and French.
-
B.
Elsa Astete Millán
Elsa Astete Millán was an Argentine woman best known as the first wife of renowned writer Jorge Luis Borges.
-
C.
Ana Martínez
Ana Martínez is known as the romantic partner of Chilean footballer Diego de Almagro.
-
D.
Marta (Spanish)
Marta is the Spanish given name equivalent to Martha, commonly used in Spanish-speaking countries.
-
E.
María
María is a key character in Ernest Hemingway's novel "For Whom the Bell Tolls," known as a young Spanish woman and love interest of the protagonist amid the Spanish Civil War.
- 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_69ad85a729d48190afd789cd8417f289 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb28a813c81909d1c71fe577e6681 |
completed | March 8, 2026, 5:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b34bbdebb88190be8458f840e2d84f |
completed | March 12, 2026, 11:26 p.m. |
Created at: March 8, 2026, 3:13 p.m.