Triple
T32092249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Romney sheep |
E819625
|
entity |
| Predicate | ramWeightRange |
P26162
|
FINISHED |
| Object | 90–120 kg (approximate) |
—
|
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: 90–120 kg (approximate) | Statement: [Romney sheep, ramWeightRange, 90–120 kg (approximate)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ramWeightRange Context triple: [Romney sheep, ramWeightRange, 90–120 kg (approximate)]
-
A.
weightRangeDescription
chosen
Indicates the textual description that specifies the range within which an entity’s weight falls.
-
B.
platformWeight
Indicates the weight or mass associated with a given platform.
-
C.
emptyWeight
Indicates the weight of an object or vehicle when it is empty, excluding any load, cargo, or passengers.
-
D.
weightSize
Indicates a relationship between an entity’s weight and its physical size, typically expressing how one varies or is characterized in terms of the other.
-
E.
availableWeights
Indicates that certain weight values or options are currently accessible or usable in a given context.
- 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_69f349004b2481908ce2e50af0d579a8 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6b63edd4c819093b664b38a69d7c8 |
completed | May 3, 2026, 2:43 a.m. |
| PD | Predicate disambiguation | batch_69f6b3a7bdb481908d16a32f49e38c2c |
completed | May 3, 2026, 2:32 a.m. |
Created at: May 1, 2026, 12:25 a.m.