Triple
T31659988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charlotte Jane |
E807971
|
entity |
| Predicate | hasLanguageOfPassengers |
P110606
|
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: [Charlotte Jane, hasLanguageOfPassengers, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageOfPassengers Context triple: [Charlotte Jane, hasLanguageOfPassengers, English]
-
A.
hasLanguageOfSurroundingCountries
Indicates that an entity uses or includes the languages commonly spoken in the countries that geographically surround it.
-
B.
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.
-
C.
hasLanguageOfSide
Indicates that an entity uses or is associated with a particular language on a specific side or aspect (e.g., one side of a bilingual object or interface).
-
D.
hasPrimaryLanguageOfVisitors
chosen
Indicates that an entity is associated with the main language typically spoken or used by its visitors.
-
E.
hasLanguageRestriction
Indicates that an entity is subject to limitations or specific conditions regarding the languages it can use, support, or be associated with.
- 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_69f348daf95c81908b4c985b7ddcd0b3 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fe610e1f6881908f10070ba64643cf |
completed | May 8, 2026, 10:17 p.m. |
| PD | Predicate disambiguation | batch_69fe604c6c008190ad659e9b9fa82f7b |
completed | May 8, 2026, 10:14 p.m. |
Created at: April 30, 2026, 10:56 p.m.