Triple
T8451082
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | She Said |
E199798
|
entity |
| Predicate | cinematographyBy |
P1953
|
FINISHED |
| Object | Natasha Braier |
E670711
|
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: Natasha Braier | Statement: [She Said, cinematographyBy, Natasha Braier]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Natasha Braier Context triple: [She Said, cinematographyBy, Natasha Braier]
-
A.
Natasha Braier
chosen
Natasha Braier is an Argentine cinematographer known for her visually distinctive work on independent and art-house films such as "The Neon Demon" and "Somers Town."
-
B.
Natasha Naginsky
Natasha Naginsky is a recurring character on the television series "Sex and the City," known as the poised and polished woman who briefly marries Mr. Big.
-
C.
Alexia Barroso
Alexia Barroso is the stepdaughter of actor Matt Damon, known for largely maintaining a private life outside of the public spotlight.
-
D.
Natasha Fuentes
Natasha Fuentes is a daughter of renowned Mexican novelist and diplomat Carlos Fuentes.
-
E.
Natasha Katz
Natasha Katz is a renowned American lighting designer celebrated for her work on numerous Broadway productions and other major theatrical and live entertainment 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_69ca8318231881908fd1bc1c4d45d286 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe44815488190a912d63512e19af0 |
completed | March 31, 2026, 3:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce39c11a488190b7775002e419eee7 |
completed | April 2, 2026, 9:41 a.m. |
Created at: March 30, 2026, 6:09 p.m.