Triple
T13120151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Giant Land |
E311698
|
entity |
| Predicate | featuresObjectType |
P5048
|
FINISHED |
| Object | ? Block |
—
|
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: ? Block | Statement: [Giant Land, featuresObjectType, ? Block]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresObjectType Context triple: [Giant Land, featuresObjectType, ? Block]
-
A.
featureType
chosen
Indicates the specific kind or category of feature that characterizes or distinguishes an entity.
-
B.
featuresStructure
Indicates that one entity possesses, exhibits, or incorporates a particular structure as a notable characteristic or component.
-
C.
featuresSample
Indicates that an entity includes or presents a particular sample as one of its components or examples.
-
D.
featuresThemeType
Indicates that something (such as a work, event, or item) has or is characterized by a particular type of theme.
-
E.
featuresModel
Indicates that one entity includes, exposes, or is characterized by a particular model as one of its defining components or capabilities.
- 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_69d806a9fe888190b081e2d9ea665d6c |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98196e69081909111407ee3d9f08e |
completed | April 10, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69d98043a74c81908648e6cd0b4c7f71 |
completed | April 10, 2026, 10:57 p.m. |
Created at: April 9, 2026, 9:06 p.m.