Triple
T27167400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Viejo Mundo |
E682814
|
entity |
| Predicate | tieneEquivalenteEnFrancés |
P7000
|
FINISHED |
| Object | Vieux Monde |
—
|
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: Vieux Monde | Statement: [Viejo Mundo, tieneEquivalenteEnFrancés, Vieux Monde]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tieneEquivalenteEnFrancés Context triple: [Viejo Mundo, tieneEquivalenteEnFrancés, Vieux Monde]
-
A.
isFrancophoneCounterpartOf
Indicates that one entity serves as the French-speaking or French-language equivalent or counterpart of another entity.
-
B.
equivalentTitleInFrench
chosen
Indicates that one entity’s title is the equivalent or corresponding title of another entity, specifically expressed in French.
-
C.
cognateInFrench
Indicates that a given word has a corresponding French word with a common etymological origin and similar form or meaning.
-
D.
languageEquivalent
Indicates that two linguistic expressions convey the same meaning or function across different languages or language varieties.
-
E.
equivalentInZapotec
Indicates that two linguistic elements are equivalent in meaning or function within the Zapotec language.
- 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_69f65876c52c8190bc889c7a67bd07f3 |
completed | May 2, 2026, 8:03 p.m. |
| PD | Predicate disambiguation | batch_69f6575d89788190aca478e4aea05a65 |
completed | May 2, 2026, 7:58 p.m. |
Created at: April 27, 2026, 9:21 a.m.