Triple
T5284549
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tierpark Gera |
E119583
|
entity |
| Predicate | hasTypeOfAnimals |
P22866
|
FINISHED |
| Object | mammals |
—
|
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: mammals | Statement: [Tierpark Gera, hasTypeOfAnimals, mammals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfAnimals Context triple: [Tierpark Gera, hasTypeOfAnimals, mammals]
-
A.
hasAnimal
Indicates that one entity possesses, keeps, or is associated with an animal.
-
B.
hasAnimalCollection
chosen
Indicates that one entity possesses or maintains a collection or group of animals associated with it.
-
C.
usesLiveAnimals
Indicates that one entity employs or incorporates live animals in performing an action, service, process, or activity involving another entity.
-
D.
hasMammalSpecies
Indicates that one entity includes, contains, or is associated with a particular mammal species as part of its composition, population, or classification.
-
E.
hasZoo
Indicates that one entity possesses, operates, or is associated with a zoo.
- 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_69bd446de5648190b313a90bd96730d2 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd8c9c72b08190947b6b955ac1bb5a |
completed | March 20, 2026, 6:06 p.m. |
| PD | Predicate disambiguation | batch_69bd844a56b48190ad743c42246e02dd |
completed | March 20, 2026, 5:30 p.m. |
Created at: March 20, 2026, 1:52 p.m.