Triple
T29109593
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Takei Island |
E736860
|
entity |
| Predicate | relativeSizeInLakeBiwa |
P202839
|
FINISHED |
| Object | small island |
—
|
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: small island | Statement: [Takei Island, relativeSizeInLakeBiwa, small island]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relativeSizeInLakeBiwa Context triple: [Takei Island, relativeSizeInLakeBiwa, small island]
-
A.
relativeSizeInJapan
Indicates how the size of one entity compares to another specifically within the context of Japan.
-
B.
relativeSizeAmongJapanMainIslands
Indicates the comparative size ranking of an island relative to the other main islands of Japan.
-
C.
relativeSizeInArchipelago
Indicates the comparative size relationship of an entity relative to other entities within the same archipelago.
-
D.
isSmallLake
Indicates that the subject is a lake characterized by relatively small size or limited surface area.
-
E.
hasApproximateLakeDepth
Indicates that an entity is associated with a lake whose depth is given as an estimated or non-exact value.
- F. None of above. chosen
Provenance (4 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_69f077ec765c81909474c88bcc8bab43 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_6a00c486d394819084fe93d5bb11ea1e |
completed | May 10, 2026, 5:46 p.m. |
| PD | Predicate disambiguation | batch_6a00c39d99d48190a94bfa057213499c |
completed | May 10, 2026, 5:42 p.m. |
| PDg | Predicate description generation | batch_6a00c48622b08190910d4dbc6db94c10 |
completed | May 10, 2026, 5:46 p.m. |
Created at: April 28, 2026, 11:17 a.m.