Triple
T32764680
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tierpark Berlin |
E837857
|
entity |
| Predicate | animalCollectionSize |
P6210
|
FINISHED |
| Object | several thousand animals |
—
|
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: several thousand animals | Statement: [Tierpark Berlin, animalCollectionSize, several thousand animals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: animalCollectionSize Context triple: [Tierpark Berlin, animalCollectionSize, several thousand animals]
-
A.
numberOfAnimals
chosen
Indicates the quantity of animals associated with a given entity or context.
-
B.
hasAnimalCollection
Indicates that one entity possesses or maintains a collection or group of animals associated with it.
-
C.
collectionSize
Indicates the total number of items contained within a specified collection.
-
D.
speciesNumber
Indicates the numerical identifier or count associated with a particular species in a given context.
-
E.
housesAnimalGroup
Indicates that a location or structure serves as a dwelling or enclosure for a group of animals.
- 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_69f34939857c8190aa9970c51feec1eb |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6d16f5cb881908eed141afaaa0b51 |
completed | May 3, 2026, 4:39 a.m. |
| PD | Predicate disambiguation | batch_69f6cfe45554819089cbbd538d992132 |
completed | May 3, 2026, 4:32 a.m. |
Created at: May 1, 2026, 1:13 a.m.