Triple
T5115406
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belgian Malinois |
E115319
|
entity |
| Predicate | maleHeightRangeCm |
P60923
|
FINISHED |
| Object | 60–66 |
—
|
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: 60–66 | Statement: [Belgian Malinois, maleHeightRangeCm, 60–66]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maleHeightRangeCm Context triple: [Belgian Malinois, maleHeightRangeCm, 60–66]
-
A.
averageMaleHeight
Indicates the typical or mean height value associated with male individuals in a given population or context.
-
B.
averageHeight
Indicates that the relationship specifies the mean height value calculated from a set of entities or measurements.
-
C.
averageBodyLengthMale
Indicates the typical or mean body length measured specifically for male individuals of a species or group.
-
D.
averageMaleShoulderHeight
Indicates the typical or mean shoulder height measured for male individuals within a given group or context.
-
E.
averageFemaleHeight
Indicates the typical or mean height value observed among female individuals in a given group or population.
- F. None of above. chosen
Provenance (4 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_69bd4441d1648190a54a533895041987 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd75ce6044819094166aebf0688665 |
completed | March 20, 2026, 4:29 p.m. |
| PD | Predicate disambiguation | batch_69bd7160d44081908cc64f3c14d28b81 |
completed | March 20, 2026, 4:10 p.m. |
| PDg | Predicate description generation | batch_69bd73089f548190834103366e24ab40 |
completed | March 20, 2026, 4:17 p.m. |
Created at: March 20, 2026, 1:41 p.m.