Triple
T23460396
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Panda District |
E568956
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Panda |
—
|
NE NERFINISHED |
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: Panda | Statement: [Panda District, capital, Panda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Panda Context triple: [Panda District, capital, Panda]
-
A.
Panda
chosen
Panda is a small town in southern Mozambique’s Inhambane Province, known primarily as a local administrative and agricultural center.
-
B.
Panda
"Panda" is a 2015 trap single by American rapper Desiigner that became a viral hit and topped the Billboard Hot 100, bringing him mainstream recognition.
-
C.
Panda Bears
Panda Bears is the nickname of the 2nd Pursuit Squadron, a U.S. military aviation unit.
-
D.
Ailuropoda melanoleuca
Ailuropoda melanoleuca is the giant panda, a distinctive black-and-white bear native to China and known for its bamboo-based diet.
-
E.
Sichuan Pandas
Sichuan Pandas was a professional Chinese basketball team that competed in the Chinese Basketball Association around the turn of the 21st century.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e2458ebd808190b3298163132cfb0b |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a69afba88190b1b1dd27d331309f |
completed | April 29, 2026, 6:35 a.m. |
Created at: April 17, 2026, 5:53 p.m.