Triple
T17521123
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Soft Actor-Critic |
E426679
|
entity |
| Predicate | comparedWith |
P278
|
FINISHED |
| Object | TD3 |
—
|
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: TD3 | Statement: [Soft Actor-Critic, comparedWith, TD3]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TD3 Context triple: [Soft Actor-Critic, comparedWith, TD3]
-
A.
TD3
chosen
TD3 (Twin Delayed Deep Deterministic Policy Gradient) is an off-policy deep reinforcement learning algorithm that improves upon DDPG by reducing overestimation bias and stabilizing training for continuous control tasks.
-
B.
TD
TD is the post-nominal abbreviation used in Ireland to denote a Teachta Dála, a member of the lower house of the Irish parliament (Dáil Éireann).
-
C.
TD
TD is the two-letter ISO 3166-1 alpha-2 country code assigned to Chad.
-
D.
TD
TD is the stock ticker symbol for The Toronto-Dominion Bank, one of Canada’s largest multinational banking and financial services institutions.
-
E.
TD
TD is a UK postcode area covering parts of the Scottish Borders and northern England, including towns such as Galashiels and Berwick-upon-Tweed.
- 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_69d889de677081909b22d2657b1f0292 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e452d23cf08190925510344fa36f57 |
completed | April 19, 2026, 3:58 a.m. |
Created at: April 10, 2026, 5:49 a.m.