Triple
T4304200
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Branxton |
E99913
|
entity |
| Predicate | nearbyTown |
P3883
|
FINISHED |
| Object | Singleton |
E72877
|
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: Singleton | Statement: [Branxton, nearbyTown, Singleton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Singleton Context triple: [Branxton, nearbyTown, Singleton]
-
A.
Singleton
chosen
Singleton is a town in the Hunter Region of New South Wales, Australia, known for its coal mining, agriculture, and proximity to the Hunter Valley wine region.
-
B.
Mono
Mono is a Native American language of the Numic branch of the Uto-Aztecan language family, traditionally spoken in parts of California.
-
C.
Mono
Mono is an open-source, cross-platform implementation of Microsoft's .NET framework that enables running .NET applications on multiple operating systems.
-
D.
Solo
Solo is a city in Central Java, Indonesia, renowned as a major center of traditional Javanese culture and batik craftsmanship.
-
E.
Solo
Solo is a 2018 Star Wars anthology film that explores the early adventures and origins of the iconic smuggler Han Solo.
- 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_69b345528ebc8190b5abc7e95094792d |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b350b8e1cc819094ce3d6f6c8da767 |
completed | March 12, 2026, 11:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5c7507f1081909cf737dff00542d9 |
completed | March 14, 2026, 8:38 p.m. |
Created at: March 12, 2026, 11:09 p.m.