Triple
T16382819
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Donte Greene |
E397849
|
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: [Donte Greene, familyName, Greene]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Greene Context triple: [Donte Greene, 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.
Cleaver Greene
Cleaver Greene is the brilliant yet self-destructive criminal defense barrister and antihero protagonist of the Australian television series "Rake."
-
C.
Eldridge
Eldridge is an English-language surname of Old English origin, borne by various notable individuals across fields such as politics, the arts, and sports.
-
D.
The Green
The Green is a small rural settlement in Cumbria, England, situated near the town of Millom in the southwestern Lake District area.
-
E.
The Green
The Green is a historic central park and community gathering space located in downtown Morristown, New Jersey.
- 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_69d87f2880b48190ae1a9673a3bbef80 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e319ddcef08190a2081855b5cf6762 |
completed | April 18, 2026, 5:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00356b00408190beab51a23011be67 |
completed | May 10, 2026, 7:36 a.m. |
Created at: April 10, 2026, 5:08 a.m.