Triple
T1412863
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | greater kudu |
E31842
|
entity |
| Predicate | averageFemaleWeight |
P1335
|
FINISHED |
| Object | 120–210 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: 120–210 kilograms | Statement: [greater kudu, averageFemaleWeight, 120–210 kilograms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: averageFemaleWeight Context triple: [greater kudu, averageFemaleWeight, 120–210 kilograms]
-
A.
averageWeight
chosen
Indicates the typical or mean weight value associated with an entity or group of entities.
-
B.
weight
Indicates a relationship where a numerical value quantifies how heavy an entity is, often used to measure or compare mass or load.
-
C.
emptyWeight
Indicates the weight of an object or vehicle when it is empty, excluding any load, cargo, or passengers.
-
D.
weightRangeDescription
Indicates the textual description that specifies the range within which an entity’s weight falls.
-
E.
estimatedHeightAtHipsInMeters
Indicates the estimated vertical height, measured in meters, of an entity at the level of its hips.
- 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_69a49919a994819086528951bc224775 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c3e3383c81909acb9c6c1c3b817a |
completed | March 1, 2026, 10:55 p.m. |
| PD | Predicate disambiguation | batch_69a4bf048b648190ab77d9b45cb4855f |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:59 p.m.