Triple
T2801406
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charles Barkley |
E53162
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Barkley |
E17584
|
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: Barkley | Statement: [Charles Barkley, familyName, Barkley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Barkley Context triple: [Charles Barkley, familyName, Barkley]
-
A.
Barkley
chosen
Barkley is a surname most notably associated with Alben W. Barkley, the 35th vice president of the United States under President Harry S. Truman.
-
B.
Shep
Shep is the station code used to identify Sheppard–Yonge station in the Toronto subway system.
-
C.
Buck
Buck is a surname most prominently associated with American sportscaster Joe Buck, known for his play-by-play commentary on major baseball and football broadcasts.
-
D.
Rufus
Rufus was a 1970s American funk and R&B band best known for launching Chaka Khan’s career and for hits like “Tell Me Something Good” and “Ain’t Nobody.”
-
E.
Merle
Merle is a given name most famously associated with American country music legend Merle Haggard.
- 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_69ab495a90788190941b6917e1eca3a6 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abde1117148190b0c98f906f1c872e |
completed | March 7, 2026, 8:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afc66d1e488190a4b85decfb38097f |
completed | March 10, 2026, 7:21 a.m. |
Created at: March 6, 2026, 9:58 p.m.