Triple
T34151428
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Negros Occidental 1st congressional district |
E876007
|
entity |
| Predicate | hasCitiesCount |
P101584
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [Negros Occidental 1st congressional district, hasCitiesCount, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCitiesCount Context triple: [Negros Occidental 1st congressional district, hasCitiesCount, 1]
-
A.
hasNumberOfComponentCities
chosen
Indicates the relationship that specifies how many component cities are contained within or associated with a given entity.
-
B.
hasNumberOfMunicipalities
Indicates the relationship that specifies how many municipalities are associated with or contained within a given administrative or geographic entity.
-
C.
hasUrbanDistrictCount
Indicates the number of urban districts associated with a given entity.
-
D.
hasCityRank
Indicates that a city holds a particular rank or position within a defined ordering or hierarchy (such as size, importance, or administrative level).
-
E.
numberOfAutonomousCities
Indicates the count of autonomous cities associated with a given entity.
- 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_69f349abaa508190a820f206620efddc |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f7bbf906d8819099020e548dd56bc9 |
completed | May 3, 2026, 9:19 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a2dcf88190a7c9e109e41267be |
completed | May 3, 2026, 9:09 p.m. |
Created at: May 1, 2026, 1:54 a.m.