Triple
T6390315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert Herbert |
E143806
|
entity |
| Predicate | residence |
P75
|
FINISHED |
| Object | Brisbane |
E14172
|
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: Brisbane | Statement: [Robert Herbert, residence, Brisbane]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brisbane Context triple: [Robert Herbert, residence, Brisbane]
-
A.
Brisbane
chosen
Brisbane is the capital and most populous city of the Australian state of Queensland, known for its subtropical climate, riverfront setting, and role as a major economic and cultural hub.
-
B.
Brisbane
Brisbane is a small city in northern San Mateo County, California, located just south of San Francisco on the lower slopes of San Bruno Mountain.
-
C.
Melbourne
Melbourne is a major Australian city known for its vibrant arts scene, diverse culture, and status as a leading center for sports and education.
-
D.
Melbourne
Melbourne is a historic market town in Derbyshire, England, known for its Georgian architecture and the notable Melbourne Hall and gardens.
-
E.
Sydney
Sydney is the spirited, fashionable young woman who serves as the central heroine of Louisa May Alcott’s novel "An Old-Fashioned Girl."
- 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_69c008db906c819096f3597d55d95432 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0687c7fdc819099cbbb937dec215e |
completed | March 22, 2026, 10:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c638536b3481908256d413563040ed |
completed | March 27, 2026, 7:57 a.m. |
Created at: March 22, 2026, 4:34 p.m.