Triple
T8688913
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Statue of Liberty replica on Île aux Cygnes |
E206234
|
entity |
| Predicate | torchType |
P84198
|
FINISHED |
| Object | raised torch |
—
|
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: raised torch | Statement: [Statue of Liberty replica on Île aux Cygnes, torchType, raised torch]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: torchType Context triple: [Statue of Liberty replica on Île aux Cygnes, torchType, raised torch]
-
A.
gpuType
Indicates the specific kind or model category of GPU associated with an entity.
-
B.
neuralEngineType
Indicates the specific kind or category of neural processing engine associated with or used by an entity.
-
C.
torchDesign
Indicates that an entity is responsible for creating or specifying the design of a torch.
-
D.
trainingDataType
Indicates the type or category of data used for training a model, system, or process.
-
E.
theoryType
Indicates the classification relationship that specifies what type or category of theory an entity belongs to.
- 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_69ca835481fc819084e33d3bc883bfa6 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc57334b0c8190903a5a1784e74791 |
completed | March 31, 2026, 11:22 p.m. |
| PD | Predicate disambiguation | batch_69cc4569f9048190b9c86b4c81103d35 |
completed | March 31, 2026, 10:06 p.m. |
| PDg | Predicate description generation | batch_69cc483f06f48190879f4702c8b4ed00 |
completed | March 31, 2026, 10:18 p.m. |
Created at: March 30, 2026, 6:33 p.m.