Triple
T8966798
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Palermo (Huila) |
E214155
|
entity |
| Predicate | geographicDirectionFromDepartmentCapital |
P85986
|
FINISHED |
| Object | north of Neiva |
—
|
LITERAL 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: north of Neiva | Statement: [Palermo (Huila), geographicDirectionFromDepartmentCapital, north of Neiva]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: geographicDirectionFromDepartmentCapital Context triple: [Palermo (Huila), geographicDirectionFromDepartmentCapital, north of Neiva]
-
A.
capitalOfDepartment
Indicates that a city or town serves as the administrative capital of a specified department (an administrative division).
-
B.
hasDepartmentCapital
Indicates that a department has a specific city designated as its capital.
-
C.
countryCapitalOfProvince
Indicates that a country serves as the capital or primary administrative center of a specified province.
-
D.
countryCapitalProvince
Indicates that a given province serves as the capital administrative region of a specified country.
-
E.
distanceToDepartmentCapital
Indicates the measured distance between a given location and the capital city of its corresponding department.
- F. None of above. chosen
Provenance (4 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_69ca839cd6008190a1546a701a56710c |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc676389948190aa78fdf6a5ae74a5 |
completed | April 1, 2026, 12:31 a.m. |
| PD | Predicate disambiguation | batch_69cc5ed9a2d48190ad11381078e823b7 |
completed | March 31, 2026, 11:55 p.m. |
| PDg | Predicate description generation | batch_69cc5fcf24348190b6b845205161c0ee |
completed | March 31, 2026, 11:59 p.m. |
Created at: March 30, 2026, 7:01 p.m.