Triple
T3379572
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Olympic Games Marathon |
E71148
|
entity |
| Predicate | qualificationStandardType |
P43031
|
FINISHED |
| Object | time standards |
—
|
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: time standards | Statement: [Olympic Games Marathon, qualificationStandardType, time standards]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: qualificationStandardType Context triple: [Olympic Games Marathon, qualificationStandardType, time standards]
-
A.
standardsType
chosen
Indicates the classification or category of standards that apply to or are associated with an entity or activity.
-
B.
trainingStandard
Indicates that one entity defines or adheres to an established set of criteria, procedures, or benchmarks used for training or instruction of another entity.
-
C.
legalStandardType
Indicates the specific type or category of legal standard that governs or applies to a given legal rule, decision, or evaluation.
-
D.
qualificationBadge
Indicates that an entity has been awarded or holds a specific qualification badge signifying a certified skill, status, or achievement.
-
E.
hasQualification
Indicates that an entity possesses a specific qualification, credential, or competency.
- 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_69ad85a7f80c8190a05e43013f298942 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb2ec38d88190be8c824daeca5ab6 |
completed | March 8, 2026, 5:33 p.m. |
| PD | Predicate disambiguation | batch_69ada434bae48190a77ea37f9274ad8f |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:14 p.m.