Triple
T19810171
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tina |
E475921
|
entity |
| Predicate | hasDiminutiveFormOf |
P456
|
FINISHED |
| Object | Valentina |
—
|
NE NERFINISHED |
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: Valentina | Statement: [Tina, hasDiminutiveFormOf, Valentina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Valentina Context triple: [Tina, hasDiminutiveFormOf, Valentina]
-
A.
Valentina
chosen
Valentina is a feminine given name of Latin origin, commonly used in various countries and associated with meanings related to strength and health.
-
B.
Valeria
Valeria is a musical artist known for recording a cover version of the dance-pop hit "Rhythm of the Night."
-
C.
Valeria
Valeria was a late Roman province in the region of Pannonia, located in what is now western Hungary and parts of neighboring countries.
-
D.
Valeria
Valeria is the honorific epithet associated with the ancient Roman legion Legio XX Valeria Victrix, reflecting its distinguished status and achievements.
-
E.
Valeria
Valeria is a character in the Mexican film "Amores perros," a successful model whose life is dramatically altered by a devastating car accident.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e51bc4208190a1c57d8c5d1b15e4 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6542ac1b48190a0cb69dbceca74da |
completed | April 20, 2026, 4:28 p.m. |
Created at: April 10, 2026, 1:50 p.m.