Triple
T3417451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Shops at Sunset Place |
E72042
|
entity |
| Predicate | typeOfBusinessDistrict |
P31781
|
FINISHED |
| Object | lifestyle center |
—
|
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: lifestyle center | Statement: [The Shops at Sunset Place, typeOfBusinessDistrict, lifestyle center]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfBusinessDistrict Context triple: [The Shops at Sunset Place, typeOfBusinessDistrict, lifestyle center]
-
A.
hasBusinessDistrict
Indicates that a place or administrative area contains or includes a designated business district within its boundaries.
-
B.
cityDistrictType
chosen
Indicates the type or classification of a city district within an urban or administrative structure.
-
C.
isInBusinessDistrict
Indicates that an entity is located within a designated business or commercial district area.
-
D.
urbanDistrictType
Indicates the classification of an urban district according to its specific type or category within an administrative or planning system.
-
E.
regionType
Indicates the classification or category of a region, specifying what kind of region it is (e.g., administrative, geographic, or functional).
- 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_69ad85ad38e48190b7660c5118a35289 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb92c20fc81909b5debced20ec083 |
completed | March 8, 2026, 6 p.m. |
| PD | Predicate disambiguation | batch_69adadfcbc38819080852c18240451c5 |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:15 p.m.