Triple
T15355748
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lego Harry Potter |
E367165
|
entity |
| Predicate | includesSetType |
P48728
|
FINISHED |
| Object | playset |
—
|
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: playset | Statement: [Lego Harry Potter, includesSetType, playset]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesSetType Context triple: [Lego Harry Potter, includesSetType, playset]
-
A.
typeOfSets
chosen
Indicates that one entity specifies or classifies the kind or category of sets to which another entity belongs.
-
B.
canonicalSetIncludes
Indicates that a canonical or standard set contains the referenced element as one of its members.
-
C.
setsIn
Indicates that one entity places or positions another entity into or within a specified container, location, or context.
-
D.
includesUniformType
Indicates that one entity contains or encompasses a specific type of uniform within its scope or composition.
-
E.
includesFeatureTypes
Indicates that an entity contains or encompasses specific types of features as part of its composition or definition.
- 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_69d85a1483788190ad93c2748e8af34b |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e2c00648190ae2325e1ee58dcfd |
completed | April 16, 2026, 1:41 a.m. |
| PD | Predicate disambiguation | batch_69deca991e5081908b0df3d1ee7d5338 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:18 a.m.