Triple
T1995252
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Linda Christian |
E43343
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Blanca |
E191275
|
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: Blanca | Statement: [Linda Christian, givenName, Blanca]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Blanca Context triple: [Linda Christian, givenName, Blanca]
-
A.
Blanca
chosen
Blanca is a feminine given name, common in Spanish-speaking cultures, that corresponds to the English and French name Blanche.
-
B.
Rosalinda
Rosalinda is a feminine given name of Spanish and Italian origin, often interpreted to mean "beautiful rose."
-
C.
Paloma
Paloma is a feminine given name of Spanish origin meaning "dove," famously borne by designer Paloma Picasso.
-
D.
Rosaura
Rosaura is a central character in Laura Esquivel’s novel "Like Water for Chocolate," known as Tita’s sister and romantic rival within the story’s intense family and culinary drama.
-
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_69a88714cf2c819081644be450b8356e |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb86537748190a2b5e3fd44ac6430 |
completed | March 7, 2026, 5:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae1fdd7b5c8190bf23a138c28857f8 |
completed | March 9, 2026, 1:18 a.m. |
Created at: March 4, 2026, 7:37 p.m.