Triple
T15570280
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vagos |
E374220
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Mira |
E374182
|
NE 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: Mira | Statement: [Vagos, borderedBy, Mira]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mira Context triple: [Vagos, borderedBy, Mira]
-
A.
Mira
Mira is a small town in northern Ecuador’s Carchi Province, known for its Andean setting and agricultural surroundings.
-
B.
Mira
chosen
Mira is a coastal municipality in central Portugal known for its beaches, lagoons, and natural landscapes.
-
C.
Mira
Mira is a town in the Veneto region of northern Italy, situated along the Brenta Canal between Venice and Padua and known for its historic Venetian villas.
-
D.
Mira
Mira is a famous red giant variable star in the constellation Cetus, known for its dramatic changes in brightness over time.
-
E.
Mira
Mira is a 1971 Belgian-Dutch drama film directed by Fons Rademakers, based on Stijn Streuvels’ novel "De Teleurgang van den Waterhoek."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d85ccd575081908909b71a3f3e3a61 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e1de0488190b3639fc25f79d343 |
completed | April 16, 2026, 2:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff4c4440a481909699a7eee25a4b24 |
completed | May 9, 2026, 3:01 p.m. |
Created at: April 10, 2026, 4:10 a.m.