Triple
T11545952
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wumpa Islands |
E273775
|
entity |
| Predicate | hasInhabitant |
P6481
|
FINISHED |
| Object | Koala Kong |
E931038
|
NE 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: Koala Kong | Statement: [Wumpa Islands, hasInhabitant, Koala Kong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Koala Kong Context triple: [Wumpa Islands, hasInhabitant, Koala Kong]
-
A.
Koala Kong
chosen
Koala Kong is a muscular, anthropomorphic koala who appears as a boss character in the Crash Bandicoot video game series.
-
B.
Moe the Kangaroo
Moe the Kangaroo is the costumed kangaroo mascot that represents the Virginia Military Institute at its athletic events and school functions.
-
C.
The Flying Kangaroo
The Flying Kangaroo is the iconic nickname and branding symbol of Qantas, Australia’s flag carrier airline.
-
D.
Zippy the kangaroo
Zippy the kangaroo is the costumed kangaroo mascot representing the University of Akron's athletic teams, particularly the Akron Zips football team.
-
E.
Reginald the Koala
Reginald the Koala is a fictional koala character portrayed as an operative working for the CIA’s domestic branch.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d6aae4dfa48190a3ab0b19a159a3c5 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d886e3ad548190b2c88332f5d919bd |
completed | April 10, 2026, 5:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e6e82153f48190ae64146d7f28b780 |
completed | April 21, 2026, 2:59 a.m. |
Created at: April 8, 2026, 9:37 p.m.