Triple
T4238667
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ate |
E94755
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | San Luis District |
E322510
|
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: San Luis District | Statement: [Ate, borderedBy, San Luis District]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: San Luis District Context triple: [Ate, borderedBy, San Luis District]
-
A.
San Luis District
chosen
San Luis District is an urban district within the Lima metropolitan area of Peru, known for its residential neighborhoods and local commercial activity.
-
B.
San Miguelito District
San Miguelito District is a densely populated urban district in central Panama that forms part of the metropolitan area of Panama City.
-
C.
San Miguel District
San Miguel District is a coastal urban district of Lima, Peru, known for its residential areas, shopping centers, and views of the Pacific Ocean.
-
D.
San Isidro District
San Isidro District is an upscale, modern financial and residential district in Lima, Peru, known for its business centers, parks, and embassies.
-
E.
San Juan de Miraflores District
San Juan de Miraflores District is a populous urban district in southern Lima, Peru, known for its residential neighborhoods and commercial activity within the metropolitan area.
- 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_69b34537cc6481909cd0a96acbb33ef7 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34e76b6e0819084d0ce137b5ba74e |
completed | March 12, 2026, 11:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5a86c95008190b11832c741a11042 |
completed | March 14, 2026, 6:26 p.m. |
Created at: March 12, 2026, 11:05 p.m.