Triple
T146342
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OpenAI |
E3337
|
entity |
| Predicate | legalStructure |
P64
|
FINISHED |
| Object | capped-profit company |
—
|
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: capped-profit company | Statement: [OpenAI, legalStructure, capped-profit company]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalStructure Context triple: [OpenAI, legalStructure, capped-profit company]
-
A.
legalForm
chosen
Indicates the specific legal structure or organizational type under which an entity is formally constituted and recognized by law.
-
B.
legalPersonality
Indicates that an entity possesses recognized legal status, enabling it to hold rights, bear obligations, and act as a subject under the law.
-
C.
legalSubject
Indicates that an entity is the bearer of legal rights, duties, or responsibilities within a legal relationship or context.
-
D.
legalDoctrine
Indicates that one legal principle, rule, or theory is being applied, referenced, or relied upon as an authoritative basis for interpreting or deciding a legal issue.
-
E.
legalContext
Indicates that the relationship or action occurs within, is shaped by, or is relevant to a specific legal framework, proceeding, or set of legal norms.
- 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_69a252868de4819080e21c9938bfe8b6 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a257eba6188190a3cf99c91bf3038f |
completed | Feb. 28, 2026, 2:50 a.m. |
| PD | Predicate disambiguation | batch_69a25656a4fc81908a87678ac3d28f93 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.