Triple
T764017
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kaiju |
E16133
|
entity |
| Predicate | visualCharacteristics |
P662
|
FINISHED |
| Object | gigantic size relative to buildings |
—
|
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: gigantic size relative to buildings | Statement: [Kaiju, visualCharacteristics, gigantic size relative to buildings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: visualCharacteristics Context triple: [Kaiju, visualCharacteristics, gigantic size relative to buildings]
-
A.
character2
Indicates that a second character entity is involved in the relationship or context defined by the predicate.
-
B.
featuresText
Indicates that an entity includes or presents a specific piece of text as one of its characteristics or contents.
-
C.
artisticCharacteristic
Indicates that one entity possesses or exhibits a particular artistic quality, style, or trait in relation to another.
-
D.
characterizedBy
chosen
Indicates that one entity possesses a defining quality, feature, or attribute expressed by another entity.
-
E.
typicalFeatures
Indicates that the related entities are characteristic or commonly occurring features or attributes of something.
- F. None of above.
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_69a493684ee48190bd43b7c78da4aec8 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a69c8c448190a036a04fd8fdd2c2 |
completed | March 1, 2026, 8:50 p.m. |
| PD | Predicate disambiguation | batch_69a4a506106081909ef97a679ff00a5a |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.