Triple
T3663121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coolamon Shire |
E77696
|
entity |
| Predicate | hasLocality |
P7943
|
FINISHED |
| Object |
Matong
Matong is a small rural locality in the Riverina region of New South Wales, Australia, known for its grain farming and surrounding agricultural landscape.
|
E377854
|
NE FINISHED |
How this triple was built (4 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: Matong | Statement: [Coolamon Shire, hasLocality, Matong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matong Context triple: [Coolamon Shire, hasLocality, Matong]
-
A.
Makoni
Makoni is a town in Zimbabwe’s Manicaland Province, known primarily as a local administrative and commercial center for the surrounding rural district.
-
B.
Monguno
Monguno is a town and local government area in Borno State, northeastern Nigeria, known for its strategic location and role in regional security dynamics.
-
C.
Mzuzu
Mzuzu is a major city in northern Malawi known as an important commercial and administrative center for the region.
-
D.
Negombo
Negombo is a coastal city in western Sri Lanka known historically as a strategic colonial port and today for its fishing industry and beach tourism.
-
E.
Sibu
Sibu is a major town in the central region of Sarawak, Malaysia, known as a commercial and transportation hub on the island of Borneo.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Matong Triple: [Coolamon Shire, hasLocality, Matong]
Generated description
Matong is a small rural locality in the Riverina region of New South Wales, Australia, known for its grain farming and surrounding agricultural landscape.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Matong Target entity description: Matong is a small rural locality in the Riverina region of New South Wales, Australia, known for its grain farming and surrounding agricultural landscape.
-
A.
Makoni
Makoni is a town in Zimbabwe’s Manicaland Province, known primarily as a local administrative and commercial center for the surrounding rural district.
-
B.
Monguno
Monguno is a town and local government area in Borno State, northeastern Nigeria, known for its strategic location and role in regional security dynamics.
-
C.
Mzuzu
Mzuzu is a major city in northern Malawi known as an important commercial and administrative center for the region.
-
D.
Negombo
Negombo is a coastal city in western Sri Lanka known historically as a strategic colonial port and today for its fishing industry and beach tourism.
-
E.
Sibu
Sibu is a major town in the central region of Sarawak, Malaysia, known as a commercial and transportation hub on the island of Borneo.
- F. None of above. chosen
Provenance (5 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_69ad85dfc4dc8190a441864202ab2a7a |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc3fcd910819082012b10b23860aa |
completed | March 8, 2026, 6:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b48846af9881909d71d63b8bd8d141 |
completed | March 13, 2026, 9:57 p.m. |
| NEDg | Description generation | batch_69b4898cae348190871b63b8aabef963 |
completed | March 13, 2026, 10:02 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b4af2032188190b29939d5dc19ccd1 |
completed | March 14, 2026, 12:43 a.m. |
Created at: March 8, 2026, 3:25 p.m.