Triple
T10529652
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North–South Railway |
E248402
|
entity |
| Predicate | connectsCapitalToLargestCity |
P35272
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [North–South Railway, connectsCapitalToLargestCity, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: connectsCapitalToLargestCity Context triple: [North–South Railway, connectsCapitalToLargestCity, yes]
-
A.
linkedToCapitalCity
Indicates a relationship where an entity is associated or connected to a capital city, typically as its relevant or corresponding urban center.
-
B.
connectsCapitalCity
chosen
Indicates a relationship where an entity is linked or associated specifically with a capital city.
-
C.
largestCity
Indicates that one city is the most populous or significant urban center within a specified region or entity.
-
D.
capitalCityAssociation
Indicates a relationship where one entity serves as the capital city of another entity, such as a country, state, or region.
-
E.
countryCapitalConnection
Indicates a relationship where a specific city serves as the official capital of a particular country.
- 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_69d381c5c7448190bec34bee7ec72bac |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d509f7d8ac8190b90c1a7f77b23545 |
completed | April 7, 2026, 1:43 p.m. |
| PD | Predicate disambiguation | batch_69d4fb94fa10819091f585bab4379c6f |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:30 p.m.