Triple
T4425237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PettingZoo |
E95191
|
entity |
| Predicate | subdomain |
P28415
|
FINISHED |
| Object | reinforcement learning |
—
|
LITERAL 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: reinforcement learning | Statement: [PettingZoo, subdomain, reinforcement learning]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subdomain Context triple: [PettingZoo, subdomain, reinforcement learning]
-
A.
secondaryDomain
Indicates that one domain functions as a secondary or auxiliary domain in relation to a primary domain.
-
B.
hasSubdomain
chosen
Indicates that one domain is a subordinate or nested part of another domain within a hierarchical naming structure.
-
C.
exampleSecondLevelDomain
Indicates that one entity is an example of a second-level domain (the part of a domain name directly below a top-level domain) associated with another entity.
-
D.
secondLevelDomain
Indicates that one entity is the second-level domain associated with, or extracted from, another entity such as a full domain name or URL.
-
E.
subtheme
Indicates that one topic or concept functions as a more specific, subordinate theme within a broader overarching theme.
- F. None of above.
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_69b3453c2a0c8190926b574c90766db9 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3554e40ec8190982acc0948da2f42 |
completed | March 13, 2026, 12:07 a.m. |
| PD | Predicate disambiguation | batch_69b34f5eabe88190a12b244ea71e46d6 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:30 p.m.