Triple
T12382653
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Timeless |
E295780
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Sak Pase |
E404782
|
NE 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: Sak Pase | Statement: [Timeless, producer, Sak Pase]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sak Pase Context triple: [Timeless, producer, Sak Pase]
-
A.
Sak Pase
chosen
Sak Pase is a music producer best known for his work in hip-hop and pop, including collaborations with major artists like Jay-Z and Kanye West.
-
B.
Saklan
Saklan is a Native American group historically associated with the Bay Miwok peoples of the San Francisco Bay Area in California.
-
C.
Sakias
Sakias is a child of the German singer and actress Nena, known for her hit song "99 Luftballons."
-
D.
Nai Sarak
Nai Sarak is a bustling commercial street in Old Delhi known for its dense concentration of bookshops, stationery stores, and educational supply outlets.
-
E.
Sakia
Sakia is a prominent cultural center and arts venue in Cairo, Egypt, known for hosting concerts, exhibitions, and a wide range of cultural events.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d6ad9e653c8190b1473c860ee53dae |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d93fbb3a2481908c2fcb5e6488eb3c |
completed | April 10, 2026, 6:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f62ac78c5c81909fb3d63bc6c9cc01 |
completed | May 2, 2026, 4:48 p.m. |
Created at: April 8, 2026, 9:54 p.m.