Triple
T2713848
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | sentimo |
E59921
|
entity |
| Predicate | unitRelationship |
P11666
|
FINISHED |
| Object | 100 sentimos = 1 Philippine peso |
—
|
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: 100 sentimos = 1 Philippine peso | Statement: [sentimo, unitRelationship, 100 sentimos = 1 Philippine peso]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: unitRelationship Context triple: [sentimo, unitRelationship, 100 sentimos = 1 Philippine peso]
-
A.
standardUnitRelation
chosen
Indicates a relationship where one unit is defined, measured, or interpreted in terms of a recognized standard unit.
-
B.
valueRelation
Indicates a comparative or associative relationship between the values or magnitudes of two or more entities.
-
C.
termRelationTo
Indicates a general relational association between one term and another, without specifying the exact nature of that relationship.
-
D.
semanticRelation
Indicates a general meaning-based connection between two entities, such as similarity, implication, or conceptual association.
-
E.
definesRelationshipBetween
Indicates that one entity specifies or establishes the nature, type, or rules of a relationship that exists between two or more other entities.
- 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_69ab4ac92a088190bc74bca14038e3de |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abda924b24819090adc4128e86d4bd |
completed | March 7, 2026, 7:58 a.m. |
| PD | Predicate disambiguation | batch_69abd8224c688190bb4a362360b03007 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:55 p.m.