Triple
T4451800
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buendía family |
E97624
|
entity |
| Predicate | languageOfFictionalContext |
P43064
|
FINISHED |
| Object | Spanish |
—
|
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 | Statement: [Buendía family, languageOfFictionalContext, Spanish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfFictionalContext Context triple: [Buendía family, languageOfFictionalContext, Spanish]
-
A.
languageOfFictionalUniverse
chosen
Indicates the language used or spoken within a fictional universe or setting.
-
B.
languageOfBooks
Indicates the language in which the referenced books are written or published.
-
C.
languageOfWritings
Indicates that a specified language is the one in which certain writings or written works are composed.
-
D.
languageSpokenOnScreen
Indicates that a particular language is used in spoken dialogue or audible communication within an on-screen work (such as a film, show, or video).
-
E.
areSpokenIn
Indicates that a particular language is used as a spoken means of communication within a specified region, community, or context.
- 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_69b3454777808190b78aa9047ba1f018 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b355f3731c81909cc5a782b12ddd38 |
completed | March 13, 2026, 12:10 a.m. |
| PD | Predicate disambiguation | batch_69b34f649df081909d3cc2f6a1b8f282 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:33 p.m.