Triple
T16516094
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Alliance |
E401187
|
entity |
| Predicate | playerSafetyEmphasis |
P123857
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [The Alliance, playerSafetyEmphasis, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: playerSafetyEmphasis Context triple: [The Alliance, playerSafetyEmphasis, yes]
-
A.
safetyRelevant
Indicates that the associated entity, condition, or information has a direct impact on safety or is critical for preventing harm or accidents.
-
B.
safetyBenefit
Indicates that one entity provides, contributes to, or results in an improvement in the safety or risk reduction experienced by another entity.
-
C.
safetyPoints
Indicates a relationship where an entity is assigned or associated with a measure of safety, typically quantified as points reflecting its safety level or performance.
-
D.
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.
-
E.
safetyImplication
Indicates that one entity has a consequence, effect, or relevance for the safety or risk level associated with another entity or situation.
- 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_69d883838abc8190bc79cb2d41733ce2 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e7bbfa481909037148cdb4d8996 |
completed | April 18, 2026, 7:10 a.m. |
| PD | Predicate disambiguation | batch_69e296995d388190b88ebe189dce890d |
completed | April 17, 2026, 8:22 p.m. |
| PDg | Predicate description generation | batch_69e2d7f97e548190a474691a152bd8e8 |
completed | April 18, 2026, 1:01 a.m. |
Created at: April 10, 2026, 5:14 a.m.