Triple
T4470347
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PPO |
E98478
|
entity |
| Predicate | relatedTo |
P37
|
FINISHED |
| Object | A3C |
E99656
|
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: A3C | Statement: [PPO, relatedTo, A3C]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: A3C Context triple: [PPO, relatedTo, A3C]
-
A.
A3C
chosen
A3C (Asynchronous Advantage Actor-Critic) is a reinforcement learning algorithm that trains multiple parallel agents to learn policies and value functions efficiently using asynchronous gradient updates.
-
B.
A2C
A2C (Advantage Actor-Critic) is a popular synchronous policy gradient reinforcement learning algorithm that combines value-based and policy-based methods to improve training stability and efficiency.
-
C.
A30
The A30 is a major trunk road in southern England that runs from London to Land's End in Cornwall, serving as an important route across the southwest.
-
D.
A3ST
A3ST is the ICAO aircraft type designator for the Airbus Beluga, a highly modified A300-600 wide-body airliner used primarily for transporting oversized cargo such as aircraft components.
-
E.
A32
A32 is an Australian state highway route designation assigned to the Mitchell Highway and associated connecting roads.
- 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_69b3454b4ae481908967426dd37284d6 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b356b6a1f48190a39f5411648c40ff |
completed | March 13, 2026, 12:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b6377154bc819099362e8b28698dbe |
completed | March 15, 2026, 4:37 a.m. |
Created at: March 12, 2026, 11:34 p.m.