Triple
T37482413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battenberg–Mountbatten line |
E931444
|
entity |
| Predicate | languageOfAnglicisedName |
P3437
|
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: [Battenberg–Mountbatten line, languageOfAnglicisedName, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfAnglicisedName Context triple: [Battenberg–Mountbatten line, languageOfAnglicisedName, English]
-
A.
hasEnglishName
chosen
Indicates that an entity is associated with a name expressed in the English language.
-
B.
languageOfHistoricName
Indicates the language in which a historic or former name of an entity is expressed.
-
C.
hasOfficialNameInEnglish
Indicates that an entity has an officially recognized name expressed in the English language.
-
D.
mainLanguageOfAlternativeName
Indicates that a specified language is the primary language in which an alternative name for an entity is expressed.
-
E.
countryNameInEnglish
Indicates the English-language name assigned to a given 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_69f76ec382248190b47844df596123c6 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a01926e2f348190a632eff5c91db5e0 |
completed | May 11, 2026, 8:25 a.m. |
| PD | Predicate disambiguation | batch_6a01923488f4819094d79a27f4bc8ab8 |
completed | May 11, 2026, 8:24 a.m. |
Created at: May 3, 2026, 4:17 p.m.