Triple
T16470315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Irish gauge |
E400041
|
entity |
| Predicate | hasExactMetricEquivalent |
P74393
|
FINISHED |
| Object | 1600 mm |
—
|
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: 1600 mm | Statement: [Irish gauge, hasExactMetricEquivalent, 1600 mm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasExactMetricEquivalent Context triple: [Irish gauge, hasExactMetricEquivalent, 1600 mm]
-
A.
hasEquivalent
Indicates that two entities are considered equal in value, meaning, or function within a given context.
-
B.
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.
-
C.
equivalentIn
Indicates that two entities are considered logically or functionally the same in meaning, status, or effect within a given context.
-
D.
isCanonicalMeasureFor
Indicates that one measure is the standard or authoritative representation used to quantify or express another measure or concept.
-
E.
isExactInSI
chosen
Indicates that a quantity or value is defined as an exact, non-approximate value within the International System of Units (SI).
- 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_69d87f2dac988190b74d6e185fa88ba4 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32dd0d2fc81909b68b5afb00f192f |
completed | April 18, 2026, 7:08 a.m. |
| PD | Predicate disambiguation | batch_69e22706b0588190a48a951c5211a617 |
completed | April 17, 2026, 12:26 p.m. |
Created at: April 10, 2026, 5:11 a.m.