Triple
T7429222
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AC-11 |
E171444
|
entity |
| Predicate | noPreservedExamples |
P76356
|
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: [AC-11, noPreservedExamples, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: noPreservedExamples Context triple: [AC-11, noPreservedExamples, true]
-
A.
hasNonExample
Indicates that something is associated with an instance that explicitly does not satisfy or illustrate a given concept, rule, or category.
-
B.
nonExample
Indicates that something is explicitly identified as not being an example or instance of a given concept, category, or pattern.
-
C.
preservedExample
Indicates that an example instance has been kept intact or maintained in its original state for future reference or use.
-
D.
hasExample
Indicates that one entity serves as an instance, illustration, or concrete example of another entity.
-
E.
notObservedIn
Indicates that a particular entity, event, or property has not been detected, recorded, or seen within a specified context, dataset, or environment.
- 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_69c68a63491881909281f73d4d5643bf |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f3082f188190af5673d18ac7e87e |
completed | March 27, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69c6f038582c8190bac77c9b5a34b862 |
completed | March 27, 2026, 9:01 p.m. |
| PDg | Predicate description generation | batch_69c6f0be2b1c8190bea06100a7caef2b |
completed | March 27, 2026, 9:03 p.m. |
Created at: March 27, 2026, 3:12 p.m.