Triple
T34918316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Freehold Raceway Mall |
E1007066
|
entity |
| Predicate | hasRegionalRank |
P13048
|
FINISHED |
| Object | one of the largest shopping malls in New Jersey |
—
|
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: one of the largest shopping malls in New Jersey | Statement: [Freehold Raceway Mall, hasRegionalRank, one of the largest shopping malls in New Jersey]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRegionalRank Context triple: [Freehold Raceway Mall, hasRegionalRank, one of the largest shopping malls in New Jersey]
-
A.
rankingRegion
Indicates the geographic or administrative region within which a ranking or ordered comparison of entities is defined or evaluated.
-
B.
hasPopulationRankInRegion
Indicates that an entity has a specific population-based rank or position within a defined geographic region.
-
C.
regionRankContext
chosen
Indicates the relative ranking or position of something within a specific geographic or regional context.
-
D.
hasRankByArea
Indicates that something is assigned a position or ranking based on its area size.
-
E.
areaRank
Indicates the relative ordering or position of an entity based on the size of its area compared to others.
- 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_69f76dc2b6b0819095a61debbd405269 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c8c34f88190ace26f555827f23e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379ff1ba081908eda86acefcf69fb |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4 p.m.