Triple
T5484469
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Soay sheep |
E123545
|
entity |
| Predicate | averageRamWeight |
P1335
|
FINISHED |
| Object | approximately 38 kilograms |
—
|
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: approximately 38 kilograms | Statement: [Soay sheep, averageRamWeight, approximately 38 kilograms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: averageRamWeight Context triple: [Soay sheep, averageRamWeight, approximately 38 kilograms]
-
A.
averageWeight
chosen
Indicates the typical or mean weight value associated with an entity or group of entities.
-
B.
emptyWeight
Indicates the weight of an object or vehicle when it is empty, excluding any load, cargo, or passengers.
-
C.
approximateWeightInPounds
Indicates the estimated weight of an entity expressed in pounds, rather than an exact measured value.
-
D.
hasRAM
Indicates that an entity possesses or is equipped with a specified amount or type of random-access memory (RAM).
-
E.
weightLimitInKilograms
Indicates the maximum allowable weight for something, expressed in kilograms.
- 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_69bd4648883481909e9775d43300c5fa |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd93e5d0f08190a6cc9fc408b7c5bb |
completed | March 20, 2026, 6:37 p.m. |
| PD | Predicate disambiguation | batch_69bd91a73b148190a865243536a4fe76 |
completed | March 20, 2026, 6:27 p.m. |
Created at: March 20, 2026, 2:10 p.m.