Triple
T5976395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zumbi (Recife) |
E133005
|
entity |
| Predicate | hasMeasurementSystem |
P1872
|
FINISHED |
| Object | metric system |
—
|
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: metric system | Statement: [Zumbi (Recife), hasMeasurementSystem, metric system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMeasurementSystem Context triple: [Zumbi (Recife), hasMeasurementSystem, metric system]
-
A.
usesMeasurementSystem
chosen
Indicates that one entity adopts or applies a particular system of measurement defined by another entity.
-
B.
hasMeasurement
Indicates that an entity is associated with a specific measured value, often including a unit or measurement context.
-
C.
isMetric
Indicates that something satisfies the properties required to be considered a metric, such as defining distances that obey non-negativity, identity, symmetry, and the triangle inequality.
-
D.
usesMetric
Indicates that one entity adopts, applies, or relies on a particular metric or measurement standard in its operation, evaluation, or description.
-
E.
typeOfMeasure
Indicates that one entity specifies the kind or category of measurement used to quantify or evaluate another entity.
- 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_69c0086f45e8819098f73dd16d45ec9d |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04dc2243c8190bd3488e7b24af985 |
completed | March 22, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69c049dcb3c081908ccc9b4d4b210229 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:04 p.m.