Triple
T5080086
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pikmin |
E114490
|
entity |
| Predicate | featuresCreatureType |
P18264
|
FINISHED |
| Object | Ice Pikmin |
E114490
|
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: Ice Pikmin | Statement: [Pikmin, featuresCreatureType, Ice Pikmin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ice Pikmin Context triple: [Pikmin, featuresCreatureType, Ice Pikmin]
-
A.
Pikmin
chosen
Pikmin is a real-time strategy and puzzle video game series featuring tiny plant-like creatures that assist players in exploring environments, solving challenges, and battling enemies.
-
B.
Pichatur
Pichatur is a town and mandal in the Tirupati district of Andhra Pradesh, India, known for its rural setting and administrative role in the region.
-
C.
Pangim
Pangim, also known as Panaji, is the riverside city that serves as the administrative and cultural center of the Indian state of Goa.
-
D.
Kodama
Kodama is a Japanese Shinkansen train service known for its all-stop, slower-speed runs along high-speed rail lines such as the Tokaido Shinkansen.
-
E.
Kodama
Kodama is a Japanese surname borne by various notable figures in fields such as politics, the military, the arts, and sports.
- 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_69bd443dbf908190a9401e9c2dc7bd7d |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd74f86c988190aa026073ed435a45 |
completed | March 20, 2026, 4:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69beb1303bc4819084e0270a8ff97aec |
completed | March 21, 2026, 2:54 p.m. |
Created at: March 20, 2026, 1:39 p.m.