Triple
T13073556
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pambujan |
E329512
|
entity |
| Predicate | hasLocalTermForMunicipality |
P53506
|
FINISHED |
| Object | bayan |
—
|
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: bayan | Statement: [Pambujan, hasLocalTermForMunicipality, bayan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLocalTermForMunicipality Context triple: [Pambujan, hasLocalTermForMunicipality, bayan]
-
A.
hasNameInMunicipality
chosen
Indicates that an entity is known by a particular name within the context or jurisdiction of a specific municipality.
-
B.
isInMunicipality
Indicates that one entity (typically a place or address) is located within the administrative boundaries of a specific municipality.
-
C.
hasMunicipalPart
Indicates that an administrative or territorial entity includes a municipality as one of its constituent parts.
-
D.
isMunicipalHomeOf
Indicates that a municipality serves as the official home base or hosting location for a particular entity or organization.
-
E.
hasMunicipalityWithCommissionedLocalAuthority
Indicates that a municipality is associated with a local authority to which it has formally commissioned certain administrative or governmental responsibilities.
- 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_69d80771749c81909a6d9197b9504872 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d981160e388190bab942a2ded2903e |
completed | April 10, 2026, 11 p.m. |
| PD | Predicate disambiguation | batch_69d9803d46688190bac6b7d208f08d01 |
completed | April 10, 2026, 10:57 p.m. |
Created at: April 9, 2026, 9 p.m.