Triple
T159992
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Diego Zoo |
E3261
|
entity |
| Predicate | numberOfSpecies |
P6211
|
FINISHED |
| Object | over 650 |
—
|
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: over 650 | Statement: [San Diego Zoo, numberOfSpecies, over 650]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfSpecies Context triple: [San Diego Zoo, numberOfSpecies, over 650]
-
A.
notableSpecies
Indicates that the subject is known for, or significantly associated with, the specified species.
-
B.
hasEndemicSpecies
Indicates that a place or region contains species that are native to and found only within that specific geographic area.
-
C.
numberOfColonies
Indicates the count of distinct colonies associated with or possessed by a given entity.
-
D.
biodiversityStatus
Indicates the current condition or level of biological diversity associated with an entity, often in terms of richness, health, or conservation concern.
-
E.
IUCNStatusSystem
Indicates the conservation status classification framework used to assign an IUCN threat category to a species or taxon.
- 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_69a2527757ec819090b8becb2cf1a862 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a25855baf48190a1b63f2e5865d957 |
completed | Feb. 28, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69a256623704819089d9eeefe05858ce |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a2578329d08190be82e004b8224d2b |
completed | Feb. 28, 2026, 2:48 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.