Triple
T17694029
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hindsight Experience Replay |
E441111
|
entity |
| Predicate | introducedBy |
P513
|
FINISHED |
| Object | Rachel Fong |
—
|
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: Rachel Fong | Statement: [Hindsight Experience Replay, introducedBy, Rachel Fong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rachel Fong Context triple: [Hindsight Experience Replay, introducedBy, Rachel Fong]
-
A.
Rachel Fong
chosen
Rachel Fong is a researcher in machine learning and reinforcement learning, known for her work on the Hindsight Experience Replay technique.
-
B.
Karen Kwan
Karen Kwan is an American figure skater and the older sister of Olympic medalist Michelle Kwan.
-
C.
Jennifer Yee
Jennifer Yee is a notable individual whose achievements have made the surname Yee recognizable in her field.
-
D.
Margaret Chung
Margaret Chung was a pioneering Chinese American physician and surgeon, widely regarded as the first Chinese American woman doctor in the United States and known for her influential role in supporting U.S. military personnel during World War II.
-
E.
Fay Chang
Fay Chang is a computer scientist known for co-authoring the influential Google Bigtable paper on large-scale distributed storage systems.
- 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_69d8b9e940b081908b862bb0e6e89b0d |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4715485d88190b9b6f347ff85d7c7 |
completed | April 19, 2026, 6:08 a.m. |
Created at: April 10, 2026, 10:04 a.m.