Triple
T24284583
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 4 × 100 metres relay |
E605635
|
entity |
| Predicate | laneAssignmentMethod |
P155684
|
FINISHED |
| Object | seeding based on qualifying times |
—
|
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: seeding based on qualifying times | Statement: [4 × 100 metres relay, laneAssignmentMethod, seeding based on qualifying times]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: laneAssignmentMethod Context triple: [4 × 100 metres relay, laneAssignmentMethod, seeding based on qualifying times]
-
A.
laneAssignment
Indicates the specific lane or set of lanes that an entity (such as a vehicle or participant) is assigned to use within a multi-lane context.
-
B.
pointAllocationMethod
Indicates how points are assigned or distributed within a given system or process.
-
C.
mobilityRule
Indicates a rule or constraint governing how an entity is allowed or able to move or change location within a given context.
-
D.
laneGrouping
Indicates a relationship where multiple lanes are associated together as a single grouped unit for joint treatment or interpretation.
-
E.
shipAssignment
Indicates the association between a ship and the specific task, route, or entity it has been assigned to.
- 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_69e295480d0c8190846fc3c2e2da1d4c |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f28f54c5948190a28207d47d6205e4 |
completed | April 29, 2026, 11:08 p.m. |
| PD | Predicate disambiguation | batch_69f1c457a2908190993824395b3c365d |
completed | April 29, 2026, 8:41 a.m. |
| PDg | Predicate description generation | batch_69f27a753ca8819095706970d368f762 |
completed | April 29, 2026, 9:39 p.m. |
Created at: April 18, 2026, 12:08 a.m.