Triple
T23046007
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert Morris |
E573878
|
entity |
| Predicate | hasFamilyName |
P18
|
FINISHED |
| Object | Morris |
—
|
NE NERFINISHED |
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: Morris | Statement: [Robert Morris, hasFamilyName, Morris]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Morris Context triple: [Robert Morris, hasFamilyName, Morris]
-
A.
Morris
Morris is the given first name of Moe Berg, the American Major League Baseball catcher who later became a World War II intelligence officer.
-
B.
Morris
chosen
Morris is a common English-language surname borne by numerous notable figures in politics, arts, sports, and other fields.
-
C.
Morris
Morris is a historic British automobile marque best known for popular mass-market cars produced throughout the 20th century.
-
D.
Morris
Morris is the given first name of M. Peter McPherson, an American academic administrator and former president of Michigan State University.
-
E.
Morris
Morris is a masculine given name of English origin that has been borne by various notable figures in fields such as politics, arts, and entertainment.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245b9c11481909d06c872214d21af |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f185192754819093a87d23371e7bbc |
completed | April 29, 2026, 4:12 a.m. |
Created at: April 17, 2026, 3:54 p.m.