Triple
T5492784
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guam Bureau of Statistics and Plans |
E123739
|
entity |
| Predicate | usesForData |
P98
|
FINISHED |
| Object | policy formulation |
—
|
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: policy formulation | Statement: [Guam Bureau of Statistics and Plans, usesForData, policy formulation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesForData Context triple: [Guam Bureau of Statistics and Plans, usesForData, policy formulation]
-
A.
usedFor
chosen
Indicates that one entity serves a purpose, function, or role in accomplishing, enabling, or supporting another entity or activity.
-
B.
usedDataFrom
Indicates that one entity utilized or relied on data originating from another entity.
-
C.
dataUse
Indicates how data is intended to be accessed, processed, or applied within a particular context or activity.
-
D.
usedDataAnalytics
Indicates that an entity applied data analytics techniques or insights in performing an action or making a decision related to another entity.
-
E.
usedWith
Indicates that one entity is typically or appropriately employed together with another entity in a combined or complementary use.
- 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_69bd464a2d908190869324ce176779c8 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd9281a0148190bb7a8dae9c991b9c |
completed | March 20, 2026, 6:31 p.m. |
| PD | Predicate disambiguation | batch_69bd91a8df6481908d1643f7342fe6f0 |
completed | March 20, 2026, 6:27 p.m. |
Created at: March 20, 2026, 2:10 p.m.