Triple
T38124821
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sango |
E952037
|
entity |
| Predicate | equivalentInCuba |
P191143
|
FINISHED |
| Object | Chango |
—
|
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: Chango | Statement: [Sango, equivalentInCuba, Chango]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: equivalentInCuba Context triple: [Sango, equivalentInCuba, Chango]
-
A.
equivalentIn
Indicates that two entities are considered logically or functionally the same in meaning, status, or effect within a given context.
-
B.
equivalentInDiaspora
Indicates that two entities are considered equivalent or correspond to each other within a diaspora context, such as representing the same role, function, or identity across different diaspora communities.
-
C.
unitInCubanAccounting
Indicates that a quantity or value is expressed using the accounting units and standards specific to the Cuban accounting system.
-
D.
nationalityEquivalent
Indicates that two entities have equivalent or corresponding nationalities, treating them as the same for nationality-based reasoning.
-
E.
equivalentInZapotec
Indicates that two linguistic elements are equivalent in meaning or function within the Zapotec 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_69f76f083548819082bd2bbf53c79e8e |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fcda3699948190adb57625bae08091 |
completed | May 7, 2026, 6:30 p.m. |
| PD | Predicate disambiguation | batch_69fcd8fd16d08190b0aca6e19a632e99 |
completed | May 7, 2026, 6:25 p.m. |
| PDg | Predicate description generation | batch_69fcda35dc048190a3c90e15230900e0 |
completed | May 7, 2026, 6:30 p.m. |
Created at: May 3, 2026, 4:21 p.m.