Triple
T4791102
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pete Best |
E106601
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Best |
E58622
|
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: Best | Statement: [Pete Best, familyName, Best]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Best Context triple: [Pete Best, familyName, Best]
-
A.
Best
chosen
Best is a common English surname borne by numerous notable individuals across sports, arts, and public life.
-
B.
Best
Best is a town and municipality in the southern Netherlands, located in the province of North Brabant near the city of Eindhoven.
-
C.
The Best
"The Best" is a powerful pop-rock anthem popularized by Tina Turner that has become one of her signature songs and an enduring inspirational hit.
-
D.
Best Five
Best Five is an annual B.League honor recognizing the five most outstanding players of the season at each position in Japan’s professional basketball league.
-
E.
Be Best
Be Best is a public awareness campaign launched by former U.S. First Lady Melania Trump focused on promoting children’s well-being, online safety, and anti-bullying efforts.
- 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_69bd43f591c881909e5a532388b0f3f3 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd65ddff388190b55071ed5cae7688 |
completed | March 20, 2026, 3:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be43e8f9dc8190b4e932d179e2f097 |
completed | March 21, 2026, 7:08 a.m. |
Created at: March 20, 2026, 1:22 p.m.