Triple
T13903693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beijing Zoo |
E334290
|
entity |
| Predicate | hasExhibitedSpecies |
P22362
|
FINISHED |
| Object | giant panda |
—
|
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: giant panda | Statement: [Beijing Zoo, hasExhibitedSpecies, giant panda]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasExhibitedSpecies Context triple: [Beijing Zoo, hasExhibitedSpecies, giant panda]
-
A.
hasExhibitSpecies
chosen
Indicates that an exhibit or display includes or features a particular species.
-
B.
hasExhibitedAt
Indicates that an entity has displayed or presented its work at a particular event, venue, or exhibition.
-
C.
hasAssociatedAnimalExhibit
Indicates that an entity is linked to a specific animal exhibit that is related or relevant to it.
-
D.
hasExhibits
Indicates that an entity (such as a museum, gallery, or event) displays or presents certain items, artworks, or objects as part of its collection or show.
-
E.
hasExhibition
Indicates that an entity organizes, hosts, or presents a particular exhibition.
- 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_69d81c5eaa9c819083b1ff8689179565 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de25db1e308190aaed6a21e443cc44 |
completed | April 14, 2026, 11:32 a.m. |
| PD | Predicate disambiguation | batch_69dd464b1ab48190ae50bfc902bf6ef7 |
completed | April 13, 2026, 7:38 p.m. |
Created at: April 9, 2026, 10:16 p.m.