Triple
T37168764
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gaysorn Village |
E920855
|
entity |
| Predicate | retailPositioning |
P187496
|
FINISHED |
| Object | upscale |
—
|
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: upscale | Statement: [Gaysorn Village, retailPositioning, upscale]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: retailPositioning Context triple: [Gaysorn Village, retailPositioning, upscale]
-
A.
retailConcept
Indicates that one entity represents a retail-related concept, model, or framework that characterizes or defines the nature of another entity’s retail activity or context.
-
B.
retailRole
Indicates a relationship where an entity holds a specific functional role or position within a retail context, such as selling, managing, or operating retail activities.
-
C.
brandPositioning
Indicates how a brand is strategically placed and perceived in the minds of its target audience relative to competitors.
-
D.
positioning
Indicates the spatial or contextual arrangement of one entity relative to another or within a given environment.
-
E.
designPositioning
Indicates the spatial or conceptual placement of a design element relative to other elements or a defined reference.
- 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_69f76ea16f288190b445aa1604d996f4 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb55de3b9c8190a7656aeab3c3ffbc |
completed | May 6, 2026, 2:53 p.m. |
| PD | Predicate disambiguation | batch_69fb35bc92e08190bff447624e2df791 |
completed | May 6, 2026, 12:36 p.m. |
| PDg | Predicate description generation | batch_69fb55dc36d08190a0634fa680e13114 |
completed | May 6, 2026, 2:53 p.m. |
Created at: May 3, 2026, 4:15 p.m.