Triple
T24640811
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laura García |
E609954
|
entity |
| Predicate | isCommonInLanguageCommunity |
P139327
|
FINISHED |
| Object | Spanish-speaking world |
—
|
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: Spanish-speaking world | Statement: [Laura García, isCommonInLanguageCommunity, Spanish-speaking world]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isCommonInLanguageCommunity Context triple: [Laura García, isCommonInLanguageCommunity, Spanish-speaking world]
-
A.
isCommonInLinguisticCommunity
chosen
Indicates that something (such as a word, expression, or linguistic feature) is widely used or frequently occurs within a particular linguistic community.
-
B.
hasLanguageCommunity
Indicates that an entity is associated with or serves a particular language community.
-
C.
hasNeighboringLanguageCommunity
Indicates that one language community is geographically or socially adjacent to another, allowing for direct contact or interaction between them.
-
D.
isWidelySpokenIn
Indicates that a language is spoken by a large portion of the population across many regions or communities within a specified area.
-
E.
hasCommonTranslationLanguage
Indicates that two entities share at least one language into which both can be or have been translated.
- 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_69e2c4d28f848190ac38c400060e943d |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f2be064ff88190b5d9e5ec75a41242 |
completed | April 30, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f2a6d0ab708190b2e3b94dd20ca76b |
completed | April 30, 2026, 12:48 a.m. |
Created at: April 18, 2026, 2:33 a.m.