Triple
T22883605
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | West Arkeen |
E567541
|
entity |
| Predicate | recordLabel |
P1500
|
FINISHED |
| Object | Zoo Entertainment |
—
|
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: Zoo Entertainment | Statement: [West Arkeen, recordLabel, Zoo Entertainment]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zoo Entertainment Context triple: [West Arkeen, recordLabel, Zoo Entertainment]
-
A.
Zoo Entertainment
chosen
Zoo Entertainment was an American record label active in the 1990s, known for releasing hip hop and alternative rock albums.
-
B.
Zoo
Zoo is the nickname of Kenneth Petty, an American music industry figure best known as the husband of rapper Nicki Minaj and for his criminal record.
-
C.
Zoo
"Zoo" is a television drama series based on James Patterson’s novel, depicting a global uprising of animals against humanity.
-
D.
Zoo
Zoo is a skateboarding level set in an animal park environment featured in the video game Tony Hawk's Pro Skater 4.
-
E.
Zoo
Zoo is a collection of dark, speculative short stories by Japanese author Otsuichi, known for its unsettling blend of horror, psychological tension, and surreal twists.
- 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_69e2458a92ec81908fc1cd5f6407d2ab |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17f5dab048190a09c725dad123472 |
completed | April 29, 2026, 3:47 a.m. |
Created at: April 17, 2026, 3:39 p.m.