Triple
T2299648
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wilt Chamberlain |
E51699
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Chamberlain |
E189072
|
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: Chamberlain | Statement: [Wilt Chamberlain, familyName, Chamberlain]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chamberlain Context triple: [Wilt Chamberlain, familyName, Chamberlain]
-
A.
Chamberlain
chosen
Chamberlain is a surname most famously associated with Neville Chamberlain, the British prime minister known for his policy of appeasement toward Nazi Germany before World War II.
-
B.
Buckley
Buckley is a surname most prominently associated with William F. Buckley Jr., the influential American conservative author and founder of National Review.
-
C.
Corwin
Corwin is a surname most notably associated with Jonathan Corwin, a judge involved in the Salem witch trials in 17th-century Massachusetts.
-
D.
Vance
Vance is a surname most prominently associated with Emmy and Tony Award–winning American actor Courtney B. Vance.
-
E.
Butler
Butler is a city in Pennsylvania that serves as the administrative and economic center of Butler County.
- 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_69a88b0a9f248190bcff941463d8f65a |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abc5ec3c948190b47ea763812a1cf5 |
completed | March 7, 2026, 6:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae7f2e338881908e09d19f469a59ce |
completed | March 9, 2026, 8:05 a.m. |
Created at: March 4, 2026, 7:49 p.m.