Triple
T37976451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IRS Form 720 |
E947436
|
entity |
| Predicate | targetFilerType |
P132779
|
FINISHED |
| Object | corporations |
—
|
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: corporations | Statement: [IRS Form 720, targetFilerType, corporations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetFilerType Context triple: [IRS Form 720, targetFilerType, corporations]
-
A.
filingTypeCode
Indicates the specific category or type of filing associated with a submitted document or record.
-
B.
typicalTargetType
chosen
Indicates the usual or most common type or category of entity that serves as the target or recipient in a given relationship or action.
-
C.
fileTypeCode
Indicates the specific classification or category code that identifies the type or format of a file.
-
D.
typicalFileType
Indicates that one entity is the usual or commonly associated file type for the other entity.
-
E.
primaryTargetType
Indicates the main category or type of entity that is the principal focus or intended recipient of an action, effect, or operation.
- 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_69f76ef7db908190bba6086673a32300 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69ff519b65f081909902ba83b775ef85 |
completed | May 9, 2026, 3:24 p.m. |
| PD | Predicate disambiguation | batch_69ff506fccdc8190bd93269589040aed |
completed | May 9, 2026, 3:19 p.m. |
Created at: May 3, 2026, 4:20 p.m.