Triple
T10079869
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Enos Loveland |
E213871
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Enos |
E786473
|
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: Enos | Statement: [Enos Loveland, givenName, Enos]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Enos Context triple: [Enos Loveland, givenName, Enos]
-
A.
Enos
chosen
Enos is a short book in the Book of Mormon that recounts the personal prayer, repentance, and spiritual transformation of the prophet Enos.
-
B.
Enos
Enos is the birth name of American billionaire businessman and sports team owner Stan Kroenke.
-
C.
Enos
Enos is a surname most notably associated with American actress Mireille Enos, known for her work in film and television.
-
D.
Roscoe
"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.
-
E.
Roscoe
Roscoe is a rural unincorporated community located in Coweta County, Georgia, known for its quiet residential character and countryside setting.
- 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_69ca839bf730819086900c323c9b8c95 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd031ce748190bb71189afd331979 |
completed | April 2, 2026, 2:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2b6550da881908fd5311e7b46ef24 |
completed | April 5, 2026, 7:21 p.m. |
Created at: March 30, 2026, 9 p.m.