Triple
T3299780
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bond University |
E69299
|
entity |
| Predicate | city |
P40
|
FINISHED |
| Object | Robina |
E93131
|
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: Robina | Statement: [Bond University, city, Robina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Robina Context triple: [Bond University, city, Robina]
-
A.
Robina
chosen
Robina is a master-planned residential and commercial suburb on the Gold Coast in Queensland, Australia, known for its large shopping centre and modern urban design.
-
B.
Robin
Robin is a given name commonly used in various cultures, often as a diminutive or variant of names like Robert.
-
C.
Robin
Robin is the disciplined and strategic leader of the Teen Titans, a young superhero team in the DC Comics universe.
-
D.
Barbara
Barbara is a feminine given name of Greek origin that has been widely used in many cultures and languages.
-
E.
Barbara
Barbara is a station on Paris Métro Line 4 serving the southern suburbs of the French capital.
- 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_69ad859e529c8190a404273f53cb487d |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb0a66fcc819093931fe7a6507723 |
completed | March 8, 2026, 5:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2f3db14ac819083182f56c60b61b2 |
completed | March 12, 2026, 5:11 p.m. |
Created at: March 8, 2026, 3:11 p.m.