Triple
T15266018
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Concord |
E364902
|
entity |
| Predicate | hasNeighbouringSuburb |
P41355
|
FINISHED |
| Object | Breakfast Point |
E303778
|
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: Breakfast Point | Statement: [Concord, hasNeighbouringSuburb, Breakfast Point]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Breakfast Point Context triple: [Concord, hasNeighbouringSuburb, Breakfast Point]
-
A.
Breakfast Point
chosen
Breakfast Point is a harbourside suburb in Sydney, Australia, known for its waterfront residential developments along the Parramatta River.
-
B.
Rocky Point
Rocky Point is a coastal headland or shoreline area located along the coast of Saint Thomas Parish in Jamaica.
-
C.
Rocky Point
Rocky Point is the English name for Puerto Peñasco, a popular beach resort city on the Gulf of California in the Mexican state of Sonora.
-
D.
Rocky Point
Rocky Point is a renowned surf break on Oahu’s North Shore known for its powerful, high-performance waves that attract skilled surfers from around the world.
-
E.
Rocky Point
Rocky Point is a themed area within SeaWorld Abu Dhabi designed to immerse visitors in a coastal, marine-life environment with related exhibits and attractions.
- 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_69d85a0f08408190b3c3259ae35d79d2 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e00851c5b88190a296b6a105d3ee30 |
completed | April 15, 2026, 9:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fee600340c8190a1888d35c2c1bc86 |
completed | May 9, 2026, 7:45 a.m. |
Created at: April 10, 2026, 3:14 a.m.