Triple
T1557735
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suyeong District |
E33247
|
entity |
| Predicate | hasNumberOfAdministrativeDong |
P30315
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [Suyeong District, hasNumberOfAdministrativeDong, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfAdministrativeDong Context triple: [Suyeong District, hasNumberOfAdministrativeDong, 5]
-
A.
hasNumberOfBarangays
Indicates the total count of barangays associated with a given administrative unit or locality.
-
B.
numberOfDistricts
Indicates the total count of districts associated with a given entity or area.
-
C.
administrativeCouncilArea
Indicates that one entity is an administrative council area within which the other entity is located or governed.
-
D.
hasAdministrativeArea
Indicates that one entity serves as the governing or jurisdictional area responsible for administering another entity.
-
E.
hasNumberOfProvinces
Indicates the total count of provinces associated with a given entity.
- 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_69a885ef9cf48190b0af0f5ce3d02231 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a9407d9d1481909597af97b16512cc |
completed | March 5, 2026, 8:36 a.m. |
| PD | Predicate disambiguation | batch_69a907b688d081908171f89010c53973 |
completed | March 5, 2026, 4:33 a.m. |
| PDg | Predicate description generation | batch_69a9407aa20881909e747f247ccec642 |
completed | March 5, 2026, 8:36 a.m. |
Created at: March 4, 2026, 7:27 p.m.