Triple
T1109258
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Talib Kweli |
E25555
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Greene |
E43976
|
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: Greene | Statement: [Talib Kweli, familyName, Greene]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Greene Context triple: [Talib Kweli, familyName, Greene]
-
A.
Greene
chosen
Greene is a common English surname borne by numerous notable figures in politics, the military, the arts, and other fields.
-
B.
Greenleaf
Greenleaf is the middle name of the 19th-century American Quaker poet and abolitionist John Greenleaf Whittier.
-
C.
Garner
Garner is a surname most notably associated with John Nance Garner, the 32nd vice president of the United States under Franklin D. Roosevelt.
-
D.
Rutledge
Rutledge is a small town in eastern Tennessee that serves as the county seat of Grainger County within the Knoxville metropolitan area.
-
E.
Hayes
Hayes is a suburban district in southeast London, England, known for its residential character and green spaces within the London Borough of Bromley.
- 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_69a49428d4448190b3b36991ceae87ce |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4ba045fd88190982e1c6278fb9ca3 |
completed | March 1, 2026, 10:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac4c4f65888190b48c2d220e62a26b |
completed | March 7, 2026, 4:03 p.m. |
Created at: March 1, 2026, 7:43 p.m.