Triple
T4466237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Opal card |
E98383
|
entity |
| Predicate | region |
P40
|
FINISHED |
| Object | Newcastle |
E83982
|
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: Newcastle | Statement: [Opal card, region, Newcastle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Newcastle Context triple: [Opal card, region, Newcastle]
-
A.
Newcastle
chosen
Newcastle is a coastal city in New South Wales, Australia, known for its busy port, beaches, and industrial heritage.
-
B.
Newcastle
Newcastle is a major industrial and commercial city in South Africa’s KwaZulu-Natal province, known for its manufacturing, coal mining, and regional service economy.
-
C.
Newcastle
Newcastle is a suburban city in King County, Washington, known for its residential neighborhoods, parks, and proximity to Bellevue and Seattle.
-
D.
Newcastle
Newcastle is a settlement within the Parish of St. Andrew, likely a small town or village in a predominantly rural Caribbean island parish.
-
E.
Newcastle
Newcastle is a seaside resort town in County Down, Northern Ireland, known for its beach and as a gateway to the Mourne Mountains.
- 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_69b3454b4ae481908967426dd37284d6 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b356991a588190be2f95fd957d7f99 |
completed | March 13, 2026, 12:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b6376c8e74819087aa2ff3e4429674 |
completed | March 15, 2026, 4:37 a.m. |
Created at: March 12, 2026, 11:34 p.m.