Triple
T19681392
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Georgina |
E472597
|
entity |
| Predicate | sharesRootWith |
P3438
|
FINISHED |
| Object | George |
—
|
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: George | Statement: [Georgina, sharesRootWith, George]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: George Context triple: [Georgina, sharesRootWith, George]
-
A.
George
George is the given name of George Black, a New Zealand politician.
-
B.
George
chosen
George is a masculine given name of Greek origin, commonly used in English-speaking countries and borne by numerous historical and contemporary figures.
-
C.
George
George is the given name of George V of Hanover, a 19th-century King of Hanover from the House of Hanover.
-
D.
George
George is a male given name commonly used in English-speaking countries and borne by numerous historical figures, including kings, presidents, and cultural icons.
-
E.
George
George is the given name of George McLeod Winsor, a British writer known for his early science fiction and mystery works.
- 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_69d8e514f2e08190ba70a4449519d218 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e641bf97348190bc31b00ed4ec6cad |
completed | April 20, 2026, 3:09 p.m. |
Created at: April 10, 2026, 1:45 p.m.