Triple
T6969427
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sri Venkateswara Creations |
E161564
|
entity |
| Predicate | hasBrandReputation |
P73564
|
FINISHED |
| Object | commercially successful banner |
—
|
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: commercially successful banner | Statement: [Sri Venkateswara Creations, hasBrandReputation, commercially successful banner]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBrandReputation Context triple: [Sri Venkateswara Creations, hasBrandReputation, commercially successful banner]
-
A.
manufacturerReputation
Indicates the perceived reliability, quality, and trustworthiness associated with a product’s manufacturer.
-
B.
fashionReputation
Indicates the perceived status or esteem an entity holds within the context of fashion, based on how its style, taste, or influence is judged by others.
-
C.
hasBrandName
Indicates that an entity is associated with or identified by a specific brand name.
-
D.
hasBrandRecognitionFor
Indicates that one entity is aware of, recognizes, or can identify the brand of another entity.
-
E.
hasBrandType
Indicates that an entity is associated with or categorized under a particular brand type or classification.
- 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_69c68853cff881908439d488924a8283 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6db1649288190a52c7dab57b3c7dc |
completed | March 27, 2026, 7:31 p.m. |
| PD | Predicate disambiguation | batch_69c6d7c262508190a7708b3d9cf23d7c |
completed | March 27, 2026, 7:17 p.m. |
| PDg | Predicate description generation | batch_69c6d8e2d7b48190b37bb13984663cde |
completed | March 27, 2026, 7:22 p.m. |
Created at: March 27, 2026, 2:30 p.m.