Triple
T22944096
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Petal |
E569817
|
entity |
| Predicate | creditBuildingMethod |
P150339
|
FINISHED |
| Object | reports to major credit bureaus |
—
|
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: reports to major credit bureaus | Statement: [Petal, creditBuildingMethod, reports to major credit bureaus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: creditBuildingMethod Context triple: [Petal, creditBuildingMethod, reports to major credit bureaus]
-
A.
creditQualityInfluencedBy
Indicates that the credit quality of one entity is affected or determined by another factor or entity.
-
B.
creditFunction
Indicates a financial role or operation through which an entity extends, manages, or utilizes credit within an economic or transactional context.
-
C.
hasCreditRating
Indicates that an entity is assigned a formal assessment of its creditworthiness, typically expressed as a credit score or rating.
-
D.
hasBureau
Indicates that an entity is associated with or possesses a specific bureau, such as an office, department, or administrative unit.
-
E.
hasAlternativeCredit
Indicates that an entity is associated with a different or substitute form of credit or credit option than the primary one.
- F. None of above. chosen
Provenance (4 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_69e2459199d08190a8184ee2aa935842 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1819b65dc8190b9456346e7284ddf |
completed | April 29, 2026, 3:57 a.m. |
| PD | Predicate disambiguation | batch_69ef3b882e708190b0eb0c87021c75b8 |
completed | April 27, 2026, 10:33 a.m. |
| PDg | Predicate description generation | batch_69ef538a115081908982597f79355840 |
completed | April 27, 2026, 12:16 p.m. |
Created at: April 17, 2026, 3:45 p.m.