Triple
T25863944
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LNER Class A4 |
E651559
|
entity |
| Predicate | preservedExamplesLocatedIn |
P58841
|
FINISHED |
| Object | United States |
—
|
NE NERFINISHED |
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: United States | Statement: [LNER Class A4, preservedExamplesLocatedIn, United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: preservedExamplesLocatedIn Context triple: [LNER Class A4, preservedExamplesLocatedIn, United States]
-
A.
locationOfExamples
chosen
Indicates that something serves as the place or context where examples of a particular type, concept, or item can be found.
-
B.
preservedExample
Indicates that an example instance has been kept intact or maintained in its original state for future reference or use.
-
C.
preservedAt
Indicates that something is kept, maintained, or conserved in a particular place or context.
-
D.
somePreservedAs
Indicates that at least one part or instance of an entity is kept or maintained in a particular state, form, or condition.
-
E.
preservedFor
Indicates that something has been kept intact or maintained in a particular state for the benefit, use, or reference of a specified entity or purpose.
- 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_69e7ab3a199c81909227cb964cacfe24 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f63fd6c68481908c542aa03e297b9c |
completed | May 2, 2026, 6:17 p.m. |
| PD | Predicate disambiguation | batch_69f63c6456608190b94e7c2e2c2a4824 |
completed | May 2, 2026, 6:03 p.m. |
Created at: April 22, 2026, 8:06 a.m.