Triple
T21228596
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amtrak enabling legislation |
E523145
|
entity |
| Predicate | legalFormOfCreatedEntity |
P64
|
FINISHED |
| Object | quasi-public corporation |
—
|
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: quasi-public corporation | Statement: [Amtrak enabling legislation, legalFormOfCreatedEntity, quasi-public corporation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalFormOfCreatedEntity Context triple: [Amtrak enabling legislation, legalFormOfCreatedEntity, quasi-public corporation]
-
A.
typicalLegalForm
Indicates the standard or commonly used legal organizational form associated with an entity.
-
B.
legalForm
chosen
Indicates the specific legal structure or organizational type under which an entity is formally constituted and recognized by law.
-
C.
legalFormedAs
Indicates that an entity was established or constituted under a specific legal structure or organizational form.
-
D.
countryLegalForm
Indicates the legal or organizational form that an entity has under the laws of a specific country.
-
E.
legalPersonality
Indicates that an entity possesses recognized legal status, enabling it to hold rights, bear obligations, and act as a subject under the law.
- 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_69e0b512ad94819087942b2ed925185f |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e734ad5068819088b203eeba4e6380 |
completed | April 21, 2026, 8:26 a.m. |
| PD | Predicate disambiguation | batch_69e5f60e1a888190ba75e2e900270a4e |
completed | April 20, 2026, 9:46 a.m. |
Created at: April 16, 2026, 3:44 p.m.