Triple
T19385065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BBB |
E484911
|
entity |
| Predicate | creditworthinessAssessment |
P66995
|
FINISHED |
| Object | adequate but not strong |
—
|
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: adequate but not strong | Statement: [BBB, creditworthinessAssessment, adequate but not strong]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: creditworthinessAssessment Context triple: [BBB, creditworthinessAssessment, adequate but not strong]
-
A.
hasCreditRating
chosen
Indicates that an entity is assigned a formal assessment of its creditworthiness, typically expressed as a credit score or rating.
-
B.
creditFunction
Indicates a financial role or operation through which an entity extends, manages, or utilizes credit within an economic or transactional context.
-
C.
creditQualityInfluencedBy
Indicates that the credit quality of one entity is affected or determined by another factor or entity.
-
D.
hasBureau
Indicates that an entity is associated with or possesses a specific bureau, such as an office, department, or administrative unit.
-
E.
hasCredit
Indicates that an entity possesses or is assigned a credit, such as financial credit, academic credit, or acknowledgment for a contribution.
- 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_69d8e8d460d88190abf0591c5c9d2b0c |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e61b3ffa548190a060d6e94562a5d2 |
completed | April 20, 2026, 12:25 p.m. |
| PD | Predicate disambiguation | batch_69e4fd602f008190aa9bc76ae17e4ce1 |
completed | April 19, 2026, 4:05 p.m. |
Created at: April 10, 2026, 1:35 p.m.