Triple
T35980645
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SKPD |
E1040552
|
entity |
| Predicate | hasServedSettlementType |
P148840
|
FINISHED |
| Object | municipal capital |
—
|
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: municipal capital | Statement: [SKPD, hasServedSettlementType, municipal capital]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasServedSettlementType Context triple: [SKPD, hasServedSettlementType, municipal capital]
-
A.
servedSettlementType
chosen
Indicates the type of settlement (e.g., city, town, village) that is provided service or coverage by a given entity.
-
B.
servesSettlement
Indicates that one entity provides services or support to a particular settlement or community.
-
C.
hasHumanSettlement
Indicates that a location or area contains or is the site of a human settlement, such as a town, village, or city.
-
D.
isInSettlementType
Indicates that one entity is located within or classified as belonging to a particular type of settlement (such as a city, town, or village).
-
E.
hasSettlementRole
Indicates that an entity holds or is assigned a specific functional role or status within a settlement.
- 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_69f76e28293c8190ae3f4e2208b87117 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a00383e868c819098fd17e25fcbdb04 |
completed | May 10, 2026, 7:48 a.m. |
| PD | Predicate disambiguation | batch_6a0037cc59688190b7b9da939a413db3 |
completed | May 10, 2026, 7:46 a.m. |
Created at: May 3, 2026, 4:07 p.m.