Triple
T37934194
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Comerío municipality |
E946300
|
entity |
| Predicate | legislativeBody |
P239
|
FINISHED |
| Object | Municipal legislature of Comerío |
—
|
NE NERFINISHED |
How this triple was built (1 step)
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: Municipal legislature of Comerío | Statement: [Comerío municipality, legislativeBody, Municipal legislature of Comerío]
Provenance (2 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_69f76ef3b7248190892fb9706423be7c |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbbd9a8c7081909cd3f285ca781eed |
completed | May 6, 2026, 10:15 p.m. |
Created at: May 3, 2026, 4:20 p.m.