Triple
T18533603
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aureliano José |
E452903
|
entity |
| Predicate | namePatternMotif |
P41002
|
FINISHED |
| Object | repetition of names in the Buendía family |
—
|
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: repetition of names in the Buendía family | Statement: [Aureliano José, namePatternMotif, repetition of names in the Buendía family]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: namePatternMotif Context triple: [Aureliano José, namePatternMotif, repetition of names in the Buendía family]
-
A.
namePattern
Indicates that an entity’s name follows or matches a specified pattern or format.
-
B.
nicknamePattern
Indicates that one entity serves as a nickname or informal name pattern for another entity.
-
C.
featuresMotif
chosen
Indicates that something contains, incorporates, or prominently includes a particular recurring motif or pattern.
-
D.
notationPattern
Indicates a recurring way in which something is symbolically represented or written, such as a consistent style or structure of notation used for an entity or concept.
-
E.
moduloPatternName
Indicates that an entity is associated with a specific naming pattern used for modulo-based grouping or partitioning.
- 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_69d8d387b5548190aa030dad2cb4947e |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e533ffc38881909f8ee132314f58a3 |
completed | April 19, 2026, 7:58 p.m. |
| PD | Predicate disambiguation | batch_69e469e0025c81908f16ed4f922674af |
completed | April 19, 2026, 5:36 a.m. |
Created at: April 10, 2026, 11:37 a.m.