Triple
T23157161
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kevin Long |
E578474
|
entity |
| Predicate | hasVideoPartsWith |
P151144
|
FINISHED |
| Object | Emerica |
—
|
NE NERFINISHED |
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: Emerica | Statement: [Kevin Long, hasVideoPartsWith, Emerica]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Emerica Context triple: [Kevin Long, hasVideoPartsWith, Emerica]
-
A.
Emerica
chosen
Emerica is a skateboarding footwear and apparel brand known for its core skate team, durable shoes, and strong presence in street and park skate culture.
-
B.
Ameria
Ameria is an ancient Umbrian town in central Italy, known today as Amelia, with significant archaeological and historical remains from pre-Roman and Roman times.
-
C.
La América
La América was a periodical associated with José Martí that played a role in disseminating his early literary and political work, including the publication of "Ismaelillo."
-
D.
Amerika
Amerika is a novel by Franz Kafka that follows a young European immigrant’s surreal and often absurd experiences in the United States.
-
E.
Amerruki
Amerruki is a Berber-language term used in Morocco, likely referring to a specific name or designation within Amazigh (Berber) culture.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69e245fb8de081908f0eba7b5fd75bc4 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18efe1b0081908e81b757d64c067c |
completed | April 29, 2026, 4:54 a.m. |
Created at: April 17, 2026, 4:01 p.m.