Triple
T3760979
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roscoe Pound |
E82159
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Roscoe |
E27970
|
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: Roscoe | Statement: [Roscoe Pound, givenName, Roscoe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roscoe Context triple: [Roscoe Pound, givenName, Roscoe]
-
A.
Roscoe
chosen
"Roscoe" is an essay by Washington Irving, included in his collection *The Sketch Book of Geoffrey Crayon, Gent.*, that reflects on the life and character of English historian and writer William Roscoe.
-
B.
Enos
Enos is the birth name of American billionaire businessman and sports team owner Stan Kroenke.
-
C.
Laurel
Laurel is a feminine given name of English origin, derived from the laurel tree traditionally associated with honor and victory.
-
D.
Ebersole
Ebersole is a surname most notably associated with American actress and singer Christine Ebersole.
-
E.
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.
- 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_69ad8b1db40081908b61ffa6b78afd4d |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcbc553a08190ba361675901496ed |
completed | March 8, 2026, 7:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4e5172abc81909cfa709ea866dc57 |
completed | March 14, 2026, 4:33 a.m. |
Created at: March 8, 2026, 3:35 p.m.