Triple
T7321816
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Solomon Loeb |
E168567
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Loeb |
E478783
|
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: Loeb | Statement: [Solomon Loeb, familyName, Loeb]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Loeb Context triple: [Solomon Loeb, familyName, Loeb]
-
A.
Loeb
chosen
Loeb is a surname most infamously associated with Richard Loeb, one of the two University of Chicago students who committed the notorious 1924 Leopold and Loeb murder.
-
B.
Hoagland
Hoagland is the given first name of American composer, pianist, singer, and actor Hoagy Carmichael.
-
C.
Melvil
Melvil is the given name of Melvil Dewey, the American librarian and educator best known for creating the Dewey Decimal Classification system.
-
D.
Goode
Goode is an English surname borne by various notable individuals across fields such as acting, politics, and academia.
-
E.
The Quigley
The Quigley is a notorious water obstacle course at the U.S. Marine Corps Officer Candidates School, known for its muddy trenches, submerged passages, and physically demanding conditions.
- 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_69c68a5251508190ad68df4151cfeb04 |
completed | March 27, 2026, 1:46 p.m. |
| NER | Named-entity recognition | batch_69c6f041f4a88190b85cff1ee5f9a6d0 |
completed | March 27, 2026, 9:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7ef01ea8c819091cd4106039c121e |
completed | March 28, 2026, 3:08 p.m. |
Created at: March 27, 2026, 3:03 p.m.