Triple
T2369027
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fiordland crested penguin |
E46046
|
entity |
| Predicate | averageHeight |
P37840
|
FINISHED |
| Object | about 60 cm |
—
|
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: about 60 cm | Statement: [Fiordland crested penguin, averageHeight, about 60 cm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: averageHeight Context triple: [Fiordland crested penguin, averageHeight, about 60 cm]
-
A.
averageMaleHeight
Indicates the typical or mean height value associated with male individuals in a given population or context.
-
B.
averageFemaleHeight
Indicates the typical or mean height value observed among female individuals in a given group or population.
-
C.
averageWeight
Indicates the typical or mean weight value associated with an entity or group of entities.
-
D.
averageMaleShoulderHeight
Indicates the typical or mean shoulder height measured for male individuals within a given group or context.
-
E.
averageAge
Indicates the mean age value calculated from a group of entities or individuals.
- F. None of above. chosen
Provenance (4 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_69a88a145268819083e2736cb835c696 |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abc76dcaa481908567a068bd61e5ad |
completed | March 7, 2026, 6:36 a.m. |
| PD | Predicate disambiguation | batch_69abc59b88348190a2d6c08f69974117 |
completed | March 7, 2026, 6:28 a.m. |
| PDg | Predicate description generation | batch_69abc6443c6c8190b932de2abd8eb28f |
completed | March 7, 2026, 6:31 a.m. |
Created at: March 4, 2026, 7:56 p.m.