Triple
T27167402
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Viejo Mundo |
E682814
|
entity |
| Predicate | tieneEquivalenteEnPortugués |
P130195
|
FINISHED |
| Object | Velho Mundo |
—
|
NE NERFINISHED |
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: Velho Mundo | Statement: [Viejo Mundo, tieneEquivalenteEnPortugués, Velho Mundo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tieneEquivalenteEnPortugués Context triple: [Viejo Mundo, tieneEquivalenteEnPortugués, Velho Mundo]
-
A.
equivalentFormInPortuguese
chosen
Indicates that one linguistic form has an equivalent expression or representation in Portuguese.
-
B.
equivalentInZapotec
Indicates that two linguistic elements are equivalent in meaning or function within the Zapotec language.
-
C.
languageEquivalent
Indicates that two linguistic expressions convey the same meaning or function across different languages or language varieties.
-
D.
hasSpanishMeaning
Indicates that one entity serves as the Spanish-language meaning or translation of another entity.
-
E.
cognateInPortuguese
Indicates that a word or term has a cognate (a related form with common etymological origin) in Portuguese.
- 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_69eefacf6e788190a75a64399d9e3109 |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f65f7731e4819099d5bd3d915ee266 |
completed | May 2, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69f65c1f94ac8190bc6fbc7916fc0d82 |
completed | May 2, 2026, 8:18 p.m. |
Created at: April 27, 2026, 9:21 a.m.