Triple
T8705800
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Come a Little Bit Closer |
E206645
|
entity |
| Predicate | hasLatinInfluence |
P84649
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Come a Little Bit Closer, hasLatinInfluence, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLatinInfluence Context triple: [Come a Little Bit Closer, hasLatinInfluence, true]
-
A.
hasSignificantSpanishInfluence
Indicates that one entity has been strongly shaped or notably affected by Spanish culture, language, practices, or presence.
-
B.
languageInfluence
Indicates that one language has an effect on the development, usage, or characteristics of another language.
-
C.
hasEthnicInfluence
Indicates that one entity has a cultural, traditional, or ethnic impact on, or contributes to shaping the ethnic character of, another entity.
-
D.
hasLinguisticHeritage
Indicates that one entity possesses or is associated with the linguistic background, tradition, or ancestry of another entity.
-
E.
languageOfInfluence
Indicates a relationship where one language has influenced the development, usage, or characteristics of another language.
- F. None of above. chosen
Provenance (4 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_69ca835645e881908f00e3c8b51da81d |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc58fcac748190a82b57aeb7c43df9 |
completed | March 31, 2026, 11:30 p.m. |
| PD | Predicate disambiguation | batch_69cc456bda508190a9aa0fb92760739e |
completed | March 31, 2026, 10:06 p.m. |
| PDg | Predicate description generation | batch_69cc582412f48190ae819965bfb0e75d |
completed | March 31, 2026, 11:26 p.m. |
Created at: March 30, 2026, 6:34 p.m.