Triple
T17363608
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cosmos (Godzilla) |
E422131
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Shobijin |
—
|
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: Shobijin | Statement: [Cosmos (Godzilla), alsoKnownAs, Shobijin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shobijin Context triple: [Cosmos (Godzilla), alsoKnownAs, Shobijin]
-
A.
Shobijin
chosen
Shobijin are the tiny twin priestesses who serve as Mothra’s mystical spokespeople and guardians in the Godzilla and broader kaiju film universe.
-
B.
Kibushi
Kibushi is a Bantu language spoken primarily in Mayotte, where it serves as one of the island’s main regional languages.
-
C.
Shinshiro
Shinshiro is a city in eastern Aichi Prefecture, Japan, known for its mountainous scenery, historic battle sites, and traditional rural landscapes.
-
D.
Yakusho
Yakusho is the family name of acclaimed Japanese actor Kōji Yakusho, known for his prominent roles in both Japanese and international cinema.
-
E.
Nishiizu
Nishiizu is a coastal town in Shizuoka Prefecture, Japan, known for its rugged seaside scenery, hot springs, and views of Suruga Bay.
- 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_69d889d520008190a26917a95bf1c2ea |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43a4f52988190847230e119a35b87 |
completed | April 19, 2026, 2:13 a.m. |
Created at: April 10, 2026, 5:44 a.m.