Triple
T16394560
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La casa verde |
E398145
|
entity |
| Predicate | settingLocation |
P40
|
FINISHED |
| Object | Piura |
E295055
|
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: Piura | Statement: [La casa verde, settingLocation, Piura]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Piura Context triple: [La casa verde, settingLocation, Piura]
-
A.
Piura
chosen
Piura is a major city in northwestern Peru known for its colonial architecture, warm climate, and role as a commercial and agricultural hub near the Pacific coast.
-
B.
Piura Region
Piura Region is a coastal region in northwestern Peru known for its warm climate, beaches, and agricultural production.
-
C.
Tumbes
Tumbes is a coastal city in northwestern Peru near the border with Ecuador, known for its mangrove forests and tropical climate.
-
D.
Chimbote
Chimbote is a coastal city in north-central Peru known for its fishing industry and port on the Pacific Ocean.
-
E.
Talara
Talara is a coastal city in northwestern Peru known for its important oil industry and nearby Pacific beaches.
- 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_69d87f2880b48190ae1a9673a3bbef80 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e3264538e4819082442d254accf392 |
completed | April 18, 2026, 6:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a003575e51c8190a8677f658eb73a30 |
completed | May 10, 2026, 7:36 a.m. |
Created at: April 10, 2026, 5:08 a.m.