Triple
T22583098
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Egyptian obelisk |
E544615
|
entity |
| Predicate | commonlyMadeOf |
P104293
|
FINISHED |
| Object | red granite |
—
|
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: red granite | Statement: [Egyptian obelisk, commonlyMadeOf, red granite]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonlyMadeOf Context triple: [Egyptian obelisk, commonlyMadeOf, red granite]
-
A.
materialFormedIn
Indicates that a material is created, produced, or formed within a specified process, environment, or context.
-
B.
materialUsed
Indicates that one entity is made from, incorporates, or utilizes the other entity as its material or substance.
-
C.
madeWith
Indicates that one entity is created, produced, or constructed using another entity as a material, ingredient, or component.
-
D.
featuresMaterialType
chosen
Indicates that an entity is characterized by or incorporates a specific type of material.
-
E.
featuresMaterialFrom
Indicates that one entity incorporates, contains, or is composed of material originating from another entity.
- 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_69e11e30d05481909df915354c89f0d6 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f15ff26d6481908cc058f8c4b87e75 |
completed | April 29, 2026, 1:33 a.m. |
| PD | Predicate disambiguation | batch_69ee626e6bb08190ada4dd8b48cc0c43 |
completed | April 26, 2026, 7:07 p.m. |
Created at: April 16, 2026, 8:53 p.m.