Triple
T7462089
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andean bear |
E176274
|
entity |
| Predicate | weightFemale |
P31786
|
FINISHED |
| Object | approximately 35 to 82 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 35 to 82 kilograms | Statement: [Andean bear, weightFemale, approximately 35 to 82 kilograms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: weightFemale Context triple: [Andean bear, weightFemale, approximately 35 to 82 kilograms]
-
A.
averageWeightFemale
chosen
Indicates the typical or mean body weight associated specifically with female individuals within a given group or context.
-
B.
averageFemaleHeight
Indicates the typical or mean height value observed among female individuals in a given group or population.
-
C.
weight
Indicates a relationship where a numerical value quantifies how heavy an entity is, often used to measure or compare mass or load.
-
D.
averageWeight
Indicates the typical or mean weight value associated with an entity or group of entities.
-
E.
femaleMass
Indicates that the subject has a mass value specifically associated with its female form or female population.
- 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_69c69f21632481908bf83f6c6da897e3 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f3d6cf8c8190a31cac121d151d78 |
completed | March 27, 2026, 9:17 p.m. |
| PD | Predicate disambiguation | batch_69c6f03bad9c8190bdd5abb86d37df47 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:39 p.m.