Triple
T19165758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Palayan City |
E469175
|
entity |
| Predicate | hasNationalSubdivisionCode |
P22016
|
FINISHED |
| Object | PH-NEC |
—
|
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: PH-NEC | Statement: [Palayan City, hasNationalSubdivisionCode, PH-NEC]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNationalSubdivisionCode Context triple: [Palayan City, hasNationalSubdivisionCode, PH-NEC]
-
A.
hasNationalSubdivisionType
Indicates that an entity is associated with a specific type or category of national-level administrative subdivision (e.g., state, province, region).
-
B.
hasSubdivisionCode
chosen
Indicates that an entity is associated with a specific code identifying one of its internal subdivisions (such as a state, province, or region).
-
C.
hasStateSubdivisionName
Indicates that an entity has a specific name for one of its internal state-level subdivisions.
-
D.
usesNumericSubdivisionCode
Indicates that one entity employs a numeric subdivision code system to identify or classify parts or regions of another entity.
-
E.
hasSubdivisionStandard
Indicates that a governing standard or specification defines how an entity is to be subdivided into smaller parts or 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_69d8dd09d5a081909ae43c286651ae5a |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5f15ee064819087f9fd822236298f |
completed | April 20, 2026, 9:26 a.m. |
| PD | Predicate disambiguation | batch_69e4b9b83d6881908e6271c620f74100 |
completed | April 19, 2026, 11:17 a.m. |
Created at: April 10, 2026, 12:06 p.m.