Triple
T4551505
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Portugal and Spain |
E110173
|
entity |
| Predicate | haveOfficialLanguageFamily |
P35817
|
FINISHED |
| Object | Romance languages |
—
|
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: Romance languages | Statement: [Portugal and Spain, haveOfficialLanguageFamily, Romance languages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: haveOfficialLanguageFamily Context triple: [Portugal and Spain, haveOfficialLanguageFamily, Romance languages]
-
A.
areOfficialLanguageFamilyOf
chosen
Indicates that one or more language families hold official status within, or are formally recognized as official for, a particular entity (such as a country or region).
-
B.
hasLanguageOfOfficialName
Indicates that an entity’s official name is expressed in a specified language.
-
C.
languageOfFamily
Indicates the language or languages commonly used or associated with a particular family.
-
D.
languageFamilyOf
Indicates that one entity is the language family to which the other entity (a specific language) belongs.
-
E.
includesMajorLanguageFamily
Indicates that one entity encompasses, contains, or is associated with a major language family as part of its scope or classification.
- 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_69bd4412524c8190be5bcc9ddee91848 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd57f7b9748190af29d02fc77b02e0 |
completed | March 20, 2026, 2:21 p.m. |
| PD | Predicate disambiguation | batch_69bd5223423c81908317351b58cff5f5 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:05 p.m.