Triple
T8319737
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eisner Award |
E194798
|
entity |
| Predicate | industryReputation |
P28647
|
FINISHED |
| Object | often compared to the Oscars for comics |
—
|
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: often compared to the Oscars for comics | Statement: [Eisner Award, industryReputation, often compared to the Oscars for comics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: industryReputation Context triple: [Eisner Award, industryReputation, often compared to the Oscars for comics]
-
A.
institutionalReputationContext
Indicates the situational or environmental factors that shape or influence an institution’s reputation.
-
B.
industryPerception
chosen
Indicates how an industry is viewed or regarded, typically in terms of reputation, trust, or overall public and stakeholder opinion.
-
C.
internationalReputation
Indicates the recognized standing, esteem, or status an entity holds within the global or international community.
-
D.
manufacturerReputation
Indicates the perceived reliability, quality, and trustworthiness associated with a product’s manufacturer.
-
E.
performanceReputation
Indicates the perceived quality or reliability of an entity’s past or expected performance as judged by others.
- 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_69ca82e7a8a88190a32bb5cc0feb012d |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7f6686a0819094abc2bfd2e500a5 |
completed | March 31, 2026, 8:01 a.m. |
| PD | Predicate disambiguation | batch_69cb70bf689c8190a9d9b6b872abf53d |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 5:55 p.m.