Triple
T516124
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ACM Prize in Computing |
E10710
|
entity |
| Predicate | areaOfRecognition |
P1597
|
FINISHED |
| Object | theoretical computer science |
—
|
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: theoretical computer science | Statement: [ACM Prize in Computing, areaOfRecognition, theoretical computer science]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: areaOfRecognition Context triple: [ACM Prize in Computing, areaOfRecognition, theoretical computer science]
-
A.
fieldOfRecognition
chosen
Indicates the domain, discipline, or area in which an entity is formally acknowledged, honored, or recognized.
-
B.
representedArea
Indicates that one entity serves as a representation or depiction of a particular area or region.
-
C.
affectedArea
Indicates the specific region or extent over which an event, condition, or influence has an impact.
-
D.
targetArea
Indicates the specific area or region that is the intended focus or destination of an action or effect.
-
E.
recognizedFor
Indicates that one entity is acknowledged, credited, or honored for a particular achievement, quality, contribution, or work associated with another entity.
- 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_69a2e84a0d08819087e01863fcd9abf1 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f184c3a481909bf60bb627b0ea88 |
completed | Feb. 28, 2026, 1:45 p.m. |
| PD | Predicate disambiguation | batch_69a2f0151e8c81909a82b58ac0515eba |
completed | Feb. 28, 2026, 1:39 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.