Triple
T1048929
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Runasimi |
E22648
|
entity |
| Predicate | statusInPeru |
P24028
|
FINISHED |
| Object | official language |
—
|
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: official language | Statement: [Runasimi, statusInPeru, official language]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: statusInPeru Context triple: [Runasimi, statusInPeru, official language]
-
A.
statusInUnitedStates
Indicates the legal or official standing that an entity holds within the jurisdiction of the United States.
-
B.
workStatusInMexico
Indicates whether an entity is authorized to work or is currently working in Mexico.
-
C.
statusInRussia
Indicates the legal, social, or operational condition or standing that something or someone has specifically within the context of Russia.
-
D.
status
Indicates the current condition, state, or standing of an entity within a given context.
-
E.
statusIndicates
Indicates that a particular status value conveys or reflects the current condition, state, or situation of an entity or process.
- 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_69a493da02e081908c13ff5e02a0fe7a |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b8f28c7c8190b9ca3749666bcbf3 |
completed | March 1, 2026, 10:08 p.m. |
| PD | Predicate disambiguation | batch_69a4b72e3e488190b768005ad647886b |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b8f1097881908932d7eea4331917 |
completed | March 1, 2026, 10:08 p.m. |
Created at: March 1, 2026, 7:42 p.m.