Triple
T4651197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Language Models are Few-Shot Learners |
E102297
|
entity |
| Predicate | author |
P4
|
FINISHED |
| Object | Ariel Herbert-Voss |
E457865
|
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: Ariel Herbert-Voss | Statement: [Language Models are Few-Shot Learners, author, Ariel Herbert-Voss]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ariel Herbert-Voss Context triple: [Language Models are Few-Shot Learners, author, Ariel Herbert-Voss]
-
A.
Ariel Herbert-Voss
chosen
Ariel Herbert-Voss is a machine learning researcher known for her work at OpenAI on large language models and AI safety.
-
B.
Tessa Berens
Tessa Berens is a fictional character from the work titled "The Silence."
-
C.
Leilani Sarelle
Leilani Sarelle is an American actress best known for her role as Roxy in the 1992 thriller film "Basic Instinct."
-
D.
Alexia Barroso
Alexia Barroso is the stepdaughter of actor Matt Damon, known for largely maintaining a private life outside of the public spotlight.
-
E.
Everly Carganilla
Everly Carganilla is a young American child actress known for roles in film and television, including the Netflix series "The Chair."
- 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_69bd43d71a308190afea7280841b0de8 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd630343f88190954d19fcd18a5864 |
completed | March 20, 2026, 3:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be0374967c8190b77bcd3ea1c4d59d |
completed | March 21, 2026, 2:33 a.m. |
Created at: March 20, 2026, 1:14 p.m.