Triple
T34387128
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Forster, New South Wales |
E882583
|
entity |
| Predicate | nearbyTown |
P3883
|
FINISHED |
| Object |
Pacific Palms, New South Wales
Pacific Palms, New South Wales is a coastal holiday locality on the Mid North Coast known for its beaches, lakes, and proximity to national parks.
|
E2095677
|
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: Pacific Palms, New South Wales | Statement: [Forster, New South Wales, nearbyTown, Pacific Palms, New South Wales]
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: Pacific Palms, New South Wales Triple: [Forster, New South Wales, nearbyTown, Pacific Palms, New South Wales]
Generated description
Pacific Palms, New South Wales is a coastal holiday locality on the Mid North Coast known for its beaches, lakes, and proximity to national parks.
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_69f349c0219881909393bbbc1edc8161 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f718783ba481908caedddcb144633e |
completed | May 3, 2026, 9:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a370dbc940c8190b21c6b3aa7e136bd |
completed | June 20, 2026, 10:01 p.m. |
| NEDg | Description generation | batch_6a370e7dcd88819091a402e550189e46 |
completed | June 20, 2026, 10:04 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a370f28a640819080ccc586b22bd785 |
completed | June 20, 2026, 10:07 p.m. |
Created at: May 1, 2026, 1:59 a.m.