Triple
T8827026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | night trains Paris–Nice |
E210039
|
entity |
| Predicate | additionalLanguagesOnBoard |
P9278
|
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: [night trains Paris–Nice, additionalLanguagesOnBoard, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: additionalLanguagesOnBoard Context triple: [night trains Paris–Nice, additionalLanguagesOnBoard, English]
-
A.
includesLanguagesSpokenAlong
Indicates that something (such as a region, route, or area) encompasses or contains the set of languages spoken along its extent or within its boundaries.
-
B.
languagesSpoken
Indicates that an entity is able to communicate using one or more specified languages.
-
C.
hasLanguages
Indicates that an entity is associated with one or more languages it uses, supports, or is expressed in.
-
D.
hasLanguageOn
chosen
Indicates that an entity uses or is associated with a particular language in a specific context, medium, or location.
-
E.
eligibleLanguage
Indicates that a particular language satisfies the required conditions to be considered valid or allowed in a given context.
- 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_69ca8365b28081909e48e45e95dfc405 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc6034e8dc819099116d772e87569a |
completed | April 1, 2026, midnight |
| PD | Predicate disambiguation | batch_69cc5c23d08481908d8c9b0ad3d1dc00 |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:46 p.m.