Triple
T18727862
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York–London |
E457952
|
entity |
| Predicate | languageMajorityOnRoute |
P11430
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [New York–London, languageMajorityOnRoute, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageMajorityOnRoute Context triple: [New York–London, languageMajorityOnRoute, English]
-
A.
languageUsedOnRoute
Indicates that a particular language is used for communication (e.g., signage, announcements, or information) along a specific route.
-
B.
majorityLanguageOf
chosen
Indicates that a given language is the primary or most widely spoken language within a specified group, region, or entity.
-
C.
languageRegionsAlongRoute
Indicates the languages spoken in the geographic regions that lie along a specified route.
-
D.
regionOfMajorLanguage
Indicates the geographic region where a particular language is predominantly spoken or holds major usage.
-
E.
languageFamilyDominant
Indicates that one language family holds a primary or prevailing status over others within a given context (such as a region, population, or system).
- 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_69d8d393ba9c8190a8b03b04ddbb0a09 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e56d74bd9881908cd314e68327c402 |
completed | April 20, 2026, 12:04 a.m. |
| PD | Predicate disambiguation | batch_69e48d03766c8190a43f7681842f4f8d |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:50 a.m.