Triple
T36532207
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ACM Autonomous Agents Research Award |
E900474
|
entity |
| Predicate | notableFieldImpact |
P194217
|
FINISHED |
| Object | advancement of autonomous agents research |
—
|
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: advancement of autonomous agents research | Statement: [ACM Autonomous Agents Research Award, notableFieldImpact, advancement of autonomous agents research]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableFieldImpact Context triple: [ACM Autonomous Agents Research Award, notableFieldImpact, advancement of autonomous agents research]
-
A.
notableImpactOn
Indicates that one entity has had a significant, recognizable, or influential effect on another entity.
-
B.
notableField
Indicates the field, discipline, or area of activity for which an entity is especially known or distinguished.
-
C.
influentialInField
chosen
Indicates that an entity has a significant impact on the development, direction, or recognition of a particular field or domain.
-
D.
notableImpression
Indicates that one entity has made a significant or memorable impact on another entity.
-
E.
recognizesImpactOn
Indicates that one entity acknowledges or understands the effect or consequences it has on another entity or situation.
- 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_69f76e5fbb388190b70c4c15573c8143 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0bf4b88190bdcfae9a14b51f0a |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:11 p.m.