Triple
T9911333
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Derbystar football |
E185150
|
entity |
| Predicate | airRetention |
P91116
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [Derbystar football, airRetention, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airRetention Context triple: [Derbystar football, airRetention, high]
-
A.
airTime
Indicates the duration or scheduling time during which something, typically a broadcast or performance, is transmitted or presented.
-
B.
leafRetention
Indicates whether an entity retains its leaves (e.g., remains evergreen) or sheds them seasonally.
-
C.
retained
Indicates that one entity keeps possession, control, or continued engagement of another entity over a period of time.
-
D.
airService
Indicates that an air transportation service (such as flights or air routes) is provided or operates between the related entities.
-
E.
retentionMethod
Indicates the method or strategy used to retain or keep something (such as data, customers, or resources) over time.
- 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_69ca8296165881908ca4750701af1f29 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cdb512a26881908eb72a21ffb1efef |
completed | April 2, 2026, 12:15 a.m. |
| PD | Predicate disambiguation | batch_69cd1d8c584081908b73de75eb18e438 |
completed | April 1, 2026, 1:28 p.m. |
| PDg | Predicate description generation | batch_69cd3581a9688190a00cef4c3eebb0ae |
completed | April 1, 2026, 3:10 p.m. |
Created at: March 30, 2026, 8:41 p.m.