Triple
T4298445
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2020 NWSL Challenge Cup |
E99772
|
entity |
| Predicate | healthSafetyMeasure |
P49797
|
FINISHED |
| Object | closed-door matches |
—
|
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: closed-door matches | Statement: [2020 NWSL Challenge Cup, healthSafetyMeasure, closed-door matches]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: healthSafetyMeasure Context triple: [2020 NWSL Challenge Cup, healthSafetyMeasure, closed-door matches]
-
A.
protectionMeasures
chosen
Indicates actions or safeguards implemented to prevent harm, damage, or risk to someone or something.
-
B.
safety
Indicates that an entity provides, ensures, or is associated with protection from harm, danger, or risk for another entity or within a given context.
-
C.
measuresSafetyUsing
Indicates that an entity evaluates or assesses safety by employing a specified method, tool, or standard.
-
D.
safetyRequirement
Indicates that one entity specifies or imposes conditions, standards, or measures necessary to ensure the safety of another entity or activity.
-
E.
safetyRelevant
Indicates that the associated entity, condition, or information has a direct impact on safety or is critical for preventing harm or accidents.
- 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_69b3455175088190aa79c6e03b86647e |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3509d39348190aa83304661230cba |
completed | March 12, 2026, 11:47 p.m. |
| PD | Predicate disambiguation | batch_69b347fe55a88190b77bab0c0f38e1aa |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:08 p.m.