Triple
T15134740
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rs |
E361524
|
entity |
| Predicate | usedInFinancialReports |
P36097
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Rs, usedInFinancialReports, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedInFinancialReports Context triple: [Rs, usedInFinancialReports, true]
-
A.
usedInFinancialDocuments
chosen
Indicates that something is employed or appears within financial documents or records.
-
B.
usedForAccounting
Indicates that something is employed in performing, supporting, or managing accounting activities or financial record-keeping.
-
C.
usedByFinancialMarket
Indicates that something is employed or utilized within the operations, practices, or mechanisms of a financial market.
-
D.
usedInTaxPayments
Indicates that something is employed or applied as part of making or fulfilling tax payments.
-
E.
areUsedIn
Indicates that certain entities serve as components, tools, or resources within a particular process, context, or application.
- 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_69d85a06450081909c5a14ea9851a15e |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e005b3f6f48190b1ed7c7b28feb7a6 |
completed | April 15, 2026, 9:40 p.m. |
| PD | Predicate disambiguation | batch_69deb9713fe881909dec2fd3f6c84b39 |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:07 a.m.