Triple
T918563
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Panda Trek |
E19826
|
entity |
| Predicate | zooSection |
P22356
|
FINISHED |
| Object | Asian Passage |
—
|
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: Asian Passage | Statement: [Panda Trek, zooSection, Asian Passage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: zooSection Context triple: [Panda Trek, zooSection, Asian Passage]
-
A.
zooAccreditation
Indicates that an entity (such as a zoo or aquarium) holds a formal accreditation or certification from a recognized accrediting organization.
-
B.
hasZoo
Indicates that one entity possesses, operates, or is associated with a zoo.
-
C.
museumSection
Indicates that one entity is a section, area, or subdivision within a museum associated with the other entity.
-
D.
fauna
Indicates that an entity is an animal or part of the animal life associated with a particular place or context.
-
E.
themeParkConnection
Indicates a relationship where two or more entities are connected through a theme park, such as by location, operation, partnership, or shared attractions.
- 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_69a493a099788190a696d9d8408cbaf4 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b388f0bc8190a087222636135ba5 |
completed | March 1, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69a4b2944ff88190a260be5355132ba5 |
completed | March 1, 2026, 9:41 p.m. |
| PDg | Predicate description generation | batch_69a4b385176081909e3e8c3f647c1fd4 |
completed | March 1, 2026, 9:45 p.m. |
Created at: March 1, 2026, 7:40 p.m.