Triple
T13514754
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Georgia Douglas Johnson |
E322730
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Bronze |
E619527
|
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: Bronze | Statement: [Georgia Douglas Johnson, notableWork, Bronze]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bronze Context triple: [Georgia Douglas Johnson, notableWork, Bronze]
-
A.
Bronze
chosen
Bronze is a metal alloy primarily composed of copper and tin, historically significant for tools, weapons, art, and coins since the Bronze Age.
-
B.
Bronze (OMBB)
Bronze (OMBB) is the bronze-class grade of South Africa’s Order of Mendi for Bravery, awarded to individuals for notable acts of courage.
-
C.
Copper
Copper is one of the animal mascots created to represent and promote the 2002 Winter Olympics in Salt Lake City.
-
D.
Copper
Copper is a period crime drama television series set in 19th-century New York City, created by Tom Fontana and others.
-
E.
The Bronze
The Bronze is a dark comedy film starring Melissa Rauch as a foul-mouthed former gymnastics star struggling with faded fame and reluctant mentorship.
- 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_69d80766a21881909f21a1b7421d3b8a |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaf87ca288190a147fbdb2f90985f |
completed | April 12, 2026, 2:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f75494642881909f33962afe26f427 |
completed | May 3, 2026, 1:58 p.m. |
Created at: April 9, 2026, 9:44 p.m.