Triple
T22397689
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nain |
E553677
|
entity |
| Predicate | carpetClassification |
P6895
|
FINISHED |
| Object | Persian city carpet |
—
|
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: Persian city carpet | Statement: [Nain, carpetClassification, Persian city carpet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: carpetClassification Context triple: [Nain, carpetClassification, Persian city carpet]
-
A.
floorType
Indicates the type or material classification of a floor associated with an entity.
-
B.
floorCharacteristic
Indicates that a specified characteristic or property is attributed to a floor or flooring surface.
-
C.
furnishingType
chosen
Indicates the type or category of furnishings associated with an entity, such as a property or room.
-
D.
hasFlooring
Indicates that one entity is equipped with or covered by a particular type of flooring material provided by another entity.
-
E.
floorUseDistribution
Indicates how the use or function of space is distributed across different floors or levels within a structure.
- 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_69e11e4da7048190b4387d422a9a0de5 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1585f67108190b8d3f23eaa0ed120 |
completed | April 29, 2026, 1:01 a.m. |
| PD | Predicate disambiguation | batch_69e73015484c8190a9a0b9f554b61a81 |
completed | April 21, 2026, 8:06 a.m. |
Created at: April 16, 2026, 8:46 p.m.