Triple
T31250352
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lord Howe Island–Sydney |
E796797
|
entity |
| Predicate | connectsRemoteAreaToMajorCity |
P197416
|
FINISHED |
| Object | true |
—
|
LITERAL 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: true | Statement: [Lord Howe Island–Sydney, connectsRemoteAreaToMajorCity, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: connectsRemoteAreaToMajorCity Context triple: [Lord Howe Island–Sydney, connectsRemoteAreaToMajorCity, true]
-
A.
connectsMajorCity
Indicates that one entity serves as a link or route providing direct connection to a major city.
-
B.
connectsMetroAreas
Indicates a relationship where a transportation route or service links two or more metropolitan areas, enabling direct travel or interaction between them.
-
C.
connectsCityTo
Indicates a relationship in which a route, infrastructure, or link joins one city to another, enabling connection or interaction between them.
-
D.
connectsCity
Indicates a relationship where one entity serves as a link or route that joins or provides direct access between two cities.
-
E.
connectsMajorCityState
Indicates that something serves as a link or route between a major city and the state it belongs to.
- F. None of above. chosen
Provenance (4 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_69f224dc84d0819081f1cb6f9127e6b1 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fe91383a1c81909266e40c3c3ede6c |
completed | May 9, 2026, 1:43 a.m. |
| PD | Predicate disambiguation | batch_69fe8fde094081908f0f121664fbb5c7 |
completed | May 9, 2026, 1:37 a.m. |
| PDg | Predicate description generation | batch_69fe9137730c81909d1d57c30566c89a |
completed | May 9, 2026, 1:43 a.m. |
Created at: April 29, 2026, 9:11 p.m.