Triple
T22109213
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Castelo de Abrantes |
E546370
|
entity |
| Predicate | locatedInHistoricalRegion |
P915
|
FINISHED |
| Object | Ribatejo |
—
|
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: Ribatejo | Statement: [Castelo de Abrantes, locatedInHistoricalRegion, Ribatejo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ribatejo Context triple: [Castelo de Abrantes, locatedInHistoricalRegion, Ribatejo]
-
A.
Ribatejo
chosen
Ribatejo is a historical province in central Portugal known for its fertile plains, agriculture, and traditional bullfighting culture.
-
B.
Potrerillos
Potrerillos is a town and municipality located in the Cortés Department of northwestern Honduras.
-
C.
Riparbella
Riparbella is a small Tuscan hill town in central Italy, known for its rural landscapes, vineyards, and traditional agricultural economy.
-
D.
Turrubares
Turrubares is a rural canton in Costa Rica known for its mountainous landscapes, agricultural activities, and low population density.
-
E.
Negrete
Negrete is a small town and commune in Chile’s Biobío Region, known for its rural character and location near the Biobío River.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69e11e378dc08190896d6a51597afd5a |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1291b9c988190b3ddd06d1f40dc78 |
completed | April 28, 2026, 9:39 p.m. |
Created at: April 16, 2026, 8:30 p.m.