Triple
T27707332
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Form W-9 |
E698588
|
entity |
| Predicate | hasInstructions |
P69226
|
FINISHED |
| Object | Instructions for the Requester of Form W-9 |
—
|
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: Instructions for the Requester of Form W-9 | Statement: [Form W-9, hasInstructions, Instructions for the Requester of Form W-9]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInstructions Context triple: [Form W-9, hasInstructions, Instructions for the Requester of Form W-9]
-
A.
hasInstructionModel
Indicates that one entity is associated with, or utilizes, a specific instruction-oriented model to guide its behavior or processing.
-
B.
includesInstruction
chosen
Indicates that one entity contains, provides, or embeds an instruction or set of instructions directed toward another entity.
-
C.
canInstruct
Indicates that one entity has the authority or ability to give instructions or guidance to another entity.
-
D.
hasInstructionSet
Indicates that one entity (typically a processor or system) is defined as using or supporting a particular instruction set.
-
E.
languageOfInstructions
Indicates that one entity specifies the language in which instructions or guidance are provided for another entity.
- 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_69ef590f655c81909f93893b3b3219b2 |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69fd3a69f1e08190a11aed015bff0858 |
completed | May 8, 2026, 1:20 a.m. |
| PD | Predicate disambiguation | batch_69fd39124180819080ca7911d3515d6d |
completed | May 8, 2026, 1:14 a.m. |
Created at: April 27, 2026, 3 p.m.