Triple
T6848680
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kodiak bear |
E157958
|
entity |
| Predicate | averageFemaleWeightRange |
P31786
|
FINISHED |
| Object | 150–300 kg |
—
|
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: 150–300 kg | Statement: [Kodiak bear, averageFemaleWeightRange, 150–300 kg]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: averageFemaleWeightRange Context triple: [Kodiak bear, averageFemaleWeightRange, 150–300 kg]
-
A.
averageWeightFemale
chosen
Indicates the typical or mean body weight associated specifically with female individuals within a given group or context.
-
B.
averageWeight
Indicates the typical or mean weight value associated with an entity or group of entities.
-
C.
weightRangeDescription
Indicates the textual description that specifies the range within which an entity’s weight falls.
-
D.
averageFemaleHeight
Indicates the typical or mean height value observed among female individuals in a given group or population.
-
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_69c6882ed4c081909dc465a7cf8838be |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d7ce3e7481908e0472b8faafa473 |
completed | March 27, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_69c6d0a12834819097d7e6c0b823745e |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:20 p.m.