Triple
T25098510
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pérez Zeledón |
E628656
|
entity |
| Predicate | hasHeadCity |
P37276
|
FINISHED |
| Object | San Isidro de El General |
—
|
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: San Isidro de El General | Statement: [Pérez Zeledón, hasHeadCity, San Isidro de El General]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHeadCity Context triple: [Pérez Zeledón, hasHeadCity, San Isidro de El General]
-
A.
hasHeadOfficeCity
Indicates that an organization’s main or central administrative office is located in a particular city.
-
B.
homeCityIsSeatOf
Indicates that the person’s home city serves as the administrative or governmental seat (e.g., capital) of a larger region such as a state, province, or country.
-
C.
containsCapitalCity
chosen
Indicates that a geographic or political region includes within its boundaries the capital city associated with it.
-
D.
capitalCityHeadquarters
Indicates that the headquarters of an organization or entity is located in the capital city of a specified region or country.
-
E.
hasTargetCity
Indicates that something is directed toward, intended for, or specifically associated with a particular city as its target.
- F. None of above.
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_69e2ff3071548190b62d1ac237397197 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f621fcea1481909b6f8b3af1ee6820 |
completed | May 2, 2026, 4:10 p.m. |
| PD | Predicate disambiguation | batch_69f620dc38088190b56b2b15ed75b3c2 |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 18, 2026, 6:25 a.m.