Triple
T3660396
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central West (New South Wales) |
E77632
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object |
Warren
Warren is a rural town in the Orana region of New South Wales, Australia, known for its agriculture and proximity to the Macquarie River.
|
E378015
|
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: Warren | Statement: [Central West (New South Wales), hasTown, Warren]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Warren Context triple: [Central West (New South Wales), hasTown, Warren]
-
A.
Warren
Warren is the given name of Warren Buffett, the renowned American investor and longtime CEO of Berkshire Hathaway.
-
B.
Warren
Warren is a common English surname borne by numerous notable figures in politics, law, entertainment, and other fields.
-
C.
Warren
Warren is a large suburban city in southeast Michigan known for its extensive automotive and defense manufacturing industries.
-
D.
Leland
Leland is a masculine given name of English origin, historically associated with figures such as American industrialist and Stanford University founder Leland Stanford.
-
E.
Shaughnessy
Shaughnessy is an affluent residential neighbourhood in Vancouver, British Columbia, known for its large heritage homes and tree-lined streets.
- 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: Warren Triple: [Central West (New South Wales), hasTown, Warren]
Generated description
Warren is a rural town in the Orana region of New South Wales, Australia, known for its agriculture and proximity to the Macquarie River.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Warren Target entity description: Warren is a rural town in the Orana region of New South Wales, Australia, known for its agriculture and proximity to the Macquarie River.
-
A.
Warren
Warren is the given name of Warren Buffett, the renowned American investor and longtime CEO of Berkshire Hathaway.
-
B.
Warren
Warren is a common English surname borne by numerous notable figures in politics, law, entertainment, and other fields.
-
C.
Warren
Warren is a large suburban city in southeast Michigan known for its extensive automotive and defense manufacturing industries.
-
D.
Leland
Leland is a masculine given name of English origin, historically associated with figures such as American industrialist and Stanford University founder Leland Stanford.
-
E.
Shaughnessy
Shaughnessy is an affluent residential neighbourhood in Vancouver, British Columbia, known for its large heritage homes and tree-lined streets.
- 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_69adc3d6fa188190a6db5bdae7083573 |
completed | March 8, 2026, 6:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b48844a380819084c4627a95b4cb3c |
completed | March 13, 2026, 9:57 p.m. |
| NEDg | Description generation | batch_69b48b1e425481908da667914d1a71e6 |
completed | March 13, 2026, 10:09 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b4aefb58448190b7d34343a5dbb0f6 |
completed | March 14, 2026, 12:42 a.m. |
Created at: March 8, 2026, 3:25 p.m.