Triple
T38395958
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kapalong |
E900761
|
entity |
| Predicate | hasNationalSubdivisionName |
P108199
|
FINISHED |
| Object | Davao del Norte |
—
|
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: Davao del Norte | Statement: [Kapalong, hasNationalSubdivisionName, Davao del Norte]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNationalSubdivisionName Context triple: [Kapalong, hasNationalSubdivisionName, Davao del Norte]
-
A.
hasStateSubdivisionName
chosen
Indicates that an entity has a specific name for one of its internal state-level subdivisions.
-
B.
hasNationalSubdivisionType
Indicates that an entity is associated with a specific type or category of national-level administrative subdivision (e.g., state, province, region).
-
C.
hasSubdivisionName3
Indicates that an entity has a third-level subdivision whose name is given by the associated value.
-
D.
subdivisionCountryName
Indicates the name of the country to which a given subdivision (such as a state, province, or region) belongs.
-
E.
hasSubdivision
Indicates that one entity is divided into and contains another entity as one of its constituent parts or administrative units.
- 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_69f76e6071a081909eea7a670d21420c |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69ffe613c03481909f3043ec8bf0bed9 |
completed | May 10, 2026, 1:57 a.m. |
| PD | Predicate disambiguation | batch_69ffe4a73fb4819091600725a443981a |
completed | May 10, 2026, 1:51 a.m. |
Created at: May 3, 2026, 4:31 p.m.