Triple
T4135627
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Equifax Inc. |
E85146
|
entity |
| Predicate | dataTypesCollected |
P4241
|
FINISHED |
| Object | Credit history |
—
|
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: Credit history | Statement: [Equifax Inc., dataTypesCollected, Credit history]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dataTypesCollected Context triple: [Equifax Inc., dataTypesCollected, Credit history]
-
A.
dataTypeCollected
chosen
Indicates that a specific type or category of data is gathered or recorded in the context of an entity or process.
-
B.
dataTypes
Indicates that one entity specifies or defines the kinds or formats of data that are valid or expected for another entity.
-
C.
datumType
Indicates the specific kind or category of data that characterizes or classifies a datum.
-
D.
storesDataType
Indicates that an entity is designed to hold, manage, or persist information of a specified data type.
-
E.
dataModel
Indicates a relationship where an entity defines, uses, or is structured according to a specific data model or schema.
- 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_69aed935ccd881909dc61f81bcdb7a78 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af03a0f3408190adba7a8513bd3d12 |
completed | March 9, 2026, 5:30 p.m. |
| PD | Predicate disambiguation | batch_69af018a54848190987f18c066c75068 |
completed | March 9, 2026, 5:21 p.m. |
Created at: March 9, 2026, 3:43 p.m.