Triple
T13138797
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vicky |
E312155
|
entity |
| Predicate | contrastsWith |
P278
|
FINISHED |
| Object | Cristina |
E316600
|
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: Cristina | Statement: [Vicky, contrastsWith, Cristina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cristina Context triple: [Vicky, contrastsWith, Cristina]
-
A.
Cristina
chosen
Cristina is one of the two free-spirited American women at the center of Woody Allen’s romantic drama film "Vicky Cristina Barcelona."
-
B.
Cristina
Cristina is a Spanish infanta and member of the Spanish royal family, known as the daughter of former King Juan Carlos I and Queen Sofía.
-
C.
Cristina
Cristina is the wife of Brazilian basketball legend Oscar Schmidt.
-
D.
Cristina
Cristina is a fictional cardiothoracic surgeon from the television series "Grey's Anatomy," known for her ambition, skill, and emotionally complex personality.
-
E.
Cristina
Cristina is a poem by Robert Browning included in his collection "Dramatic Romances and Lyrics."
- 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_69d806aabde48190899e13e41659cae5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d981b6a4348190b9922ed255759078 |
completed | April 10, 2026, 11:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f716bcbd188190ac74560a5f9e3654 |
completed | May 3, 2026, 9:34 a.m. |
Created at: April 9, 2026, 9:09 p.m.