Triple
T11943942
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A8 |
E284246
|
entity |
| Predicate | typicallyConnects |
P51738
|
FINISHED |
| Object | cities |
—
|
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: cities | Statement: [A8, typicallyConnects, cities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicallyConnects Context triple: [A8, typicallyConnects, cities]
-
A.
connectsTo
Indicates a relationship where one entity is linked or joined to another, allowing interaction, communication, or transfer between them.
-
B.
connectsUnder
Indicates that one entity forms a connection to another entity by passing beneath or under it.
-
C.
connectsPartOf
Indicates a relationship where one entity serves to link or join a component to the larger whole of which that component is a part.
-
D.
connectedByStraitTo
Indicates that one entity is geographically linked to another by a narrow body of water known as a strait.
-
E.
connectsLocation
chosen
Indicates a relationship where one entity serves as a link or route that joins or provides access between two locations.
- F. None of above.
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_69d6ab2db38c8190b1f0ed6663ef8ada |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9034444488190925a6fa6c856ed08 |
completed | April 10, 2026, 2:03 p.m. |
| PD | Predicate disambiguation | batch_69d8bb3e48e08190b2fee43af4f57323 |
completed | April 10, 2026, 8:56 a.m. |
Created at: April 8, 2026, 9:45 p.m.