Triple
T28402567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PFC Botev Plovdiv |
E719428
|
entity |
| Predicate | homeCityIsSecondLargestIn |
P2968
|
FINISHED |
| Object | Bulgaria |
—
|
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: Bulgaria | Statement: [PFC Botev Plovdiv, homeCityIsSecondLargestIn, Bulgaria]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: homeCityIsSecondLargestIn Context triple: [PFC Botev Plovdiv, homeCityIsSecondLargestIn, Bulgaria]
-
A.
hasSecondaryCity
Indicates that an entity possesses or is associated with a secondary city in addition to its primary city.
-
B.
isSecondMostPopulousCityIn
chosen
Indicates that a city is the second most populous city within a specified larger region or country.
-
C.
secondLargestMetropolitanArea
Indicates that one entity is the second largest metropolitan area (by population or size, as context defines) within the scope defined by the other entity.
-
D.
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.
-
E.
homeCityOf
Indicates that a particular city is the primary place of residence or origin for a given person or organization.
- 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_69eff6efd1b08190ae3cefd4f11388a2 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f6645ba71c81908044ade6ab577018 |
completed | May 2, 2026, 8:53 p.m. |
| PD | Predicate disambiguation | batch_69f663362c008190a22afed262f1e426 |
completed | May 2, 2026, 8:48 p.m. |
Created at: April 28, 2026, 1:21 a.m.