Triple
T32520511
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FPS |
E831167
|
entity |
| Predicate | exampleEntity |
P174907
|
FINISHED |
| Object | FPS Finance |
—
|
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: FPS Finance | Statement: [FPS, exampleEntity, FPS Finance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: exampleEntity Context triple: [FPS, exampleEntity, FPS Finance]
-
A.
exampleType
Indicates that one entity serves as a representative or illustrative instance of the type or category defined by another entity.
-
B.
hasEntity
Indicates that one entity includes, contains, or is associated with another entity as part of its composition or context.
-
C.
definesEntity
Indicates that one entity specifies, determines, or establishes the identity, nature, or boundaries of another entity.
-
D.
formsEntity
Indicates that one entity creates, shapes, or constitutes another entity as a result or outcome.
-
E.
exampleClass
Indicates that the subject belongs to, is categorized under, or serves as an instance of a particular class or type.
- 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_69f34923e1548190be0524205d8cdf8f |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c90790788190a1ed09adc86ed22d |
completed | May 3, 2026, 4:03 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f42fbc8190a06eb1044c9e6094 |
completed | May 3, 2026, 3:41 a.m. |
| PDg | Predicate description generation | batch_69f6c814c26c81908f5c47285129ff2a |
completed | May 3, 2026, 3:59 a.m. |
Created at: May 1, 2026, 1 a.m.