Triple
T16622413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Primetime Emmy Award for Outstanding Main Title Design |
E403865
|
entity |
| Predicate | hasCriterion |
P4187
|
FINISHED |
| Object | integration of typography and imagery |
—
|
LITERAL FINISHED |
How this triple was built (1 step)
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: integration of typography and imagery | Statement: [Primetime Emmy Award for Outstanding Main Title Design, hasCriterion, integration of typography and imagery]
Provenance (2 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_69d883897eb481909eaaa088ba9918d9 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3754e80ec8190b3c66b33dbc7463c |
completed | April 18, 2026, 12:13 p.m. |
Created at: April 10, 2026, 5:17 a.m.