Triple
T5115409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belgian Malinois |
E115319
|
entity |
| Predicate | femaleWeightRangeKg |
P26162
|
FINISHED |
| Object | 20–25 |
—
|
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: 20–25 | Statement: [Belgian Malinois, femaleWeightRangeKg, 20–25]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: femaleWeightRangeKg Context triple: [Belgian Malinois, femaleWeightRangeKg, 20–25]
-
A.
averageWeightFemale
Indicates the typical or mean body weight associated specifically with female individuals within a given group or context.
-
B.
weightRangeDescription
chosen
Indicates the textual description that specifies the range within which an entity’s weight falls.
-
C.
averageWeight
Indicates the typical or mean weight value associated with an entity or group of entities.
-
D.
maleBodyMass
Indicates that the relationship specifies the body mass or weight associated with a male individual.
-
E.
averageBodyLengthFemale
Indicates the typical or mean body length measured specifically for female individuals of a given group or species.
- 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_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. |
Created at: March 20, 2026, 1:41 p.m.