Triple
T13052217
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | V’Ger |
E327473
|
entity |
| Predicate | dataIntegrityIssue |
P50580
|
FINISHED |
| Object | misreading of the word "NASA" as "creator" |
—
|
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: misreading of the word "NASA" as "creator" | Statement: [V’Ger, dataIntegrityIssue, misreading of the word "NASA" as "creator"]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dataIntegrityIssue Context triple: [V’Ger, dataIntegrityIssue, misreading of the word "NASA" as "creator"]
-
A.
integrityImpact
chosen
Indicates the extent to which the relationship or action compromises, alters, or destroys the accuracy, consistency, or trustworthiness of the affected entity’s information or state.
-
B.
integrity
Indicates that an entity or relationship maintains wholeness, consistency, and freedom from corruption or unauthorized alteration.
-
C.
dataQuality
Indicates that one entity assesses or characterizes the quality, accuracy, or reliability of data associated with another entity.
-
D.
usesIntegrityCheck
Indicates that an entity employs a mechanism to verify the integrity or correctness of data, code, or operations.
-
E.
providesIntegrity
Indicates that one entity ensures the correctness, consistency, and protection from unauthorized alteration of another entity or its data.
- 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_69d8076e64308190904fb5c93517c901 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d98a9829b48190b23624b6b3df4600 |
completed | April 10, 2026, 11:41 p.m. |
| PD | Predicate disambiguation | batch_69d9803aca4c8190b1015cd159cc47a9 |
completed | April 10, 2026, 10:56 p.m. |
Created at: April 9, 2026, 8:57 p.m.