Triple
T7639579
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ostrava Zoo |
E172964
|
entity |
| Predicate | hasApproximateNumberOfAnimals |
P6210
|
FINISHED |
| Object | several thousand individual 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 individual animals | Statement: [Ostrava Zoo, hasApproximateNumberOfAnimals, several thousand individual animals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateNumberOfAnimals Context triple: [Ostrava Zoo, hasApproximateNumberOfAnimals, several thousand individual animals]
-
A.
numberOfAnimals
chosen
Indicates the quantity of animals associated with a given entity or context.
-
B.
hasHerdSize
Indicates the number of individual animals that belong to a particular herd.
-
C.
hasWildPopulationOf
Indicates that a location or area contains a naturally occurring, non-captive population of the specified species.
-
D.
hasLargeSpecies
Indicates that an entity possesses or includes at least one species that is considered large in size.
-
E.
speciesNumber
Indicates the numerical identifier or count associated with a particular species in a given context.
- 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_69c69952849881908fdcea7a93bfc307 |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6facc4b5481908697e662b0991e3f |
completed | March 27, 2026, 9:46 p.m. |
| PD | Predicate disambiguation | batch_69c6f4e8cadc8190b7977fcd213954dd |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:57 p.m.