Triple
T21837337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University Park Mall |
E539153
|
entity |
| Predicate | hasAnchorTenant |
P11754
|
FINISHED |
| Object | Forever 21 |
—
|
NE NERFINISHED |
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: Forever 21 | Statement: [University Park Mall, hasAnchorTenant, Forever 21]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Forever 21 Context triple: [University Park Mall, hasAnchorTenant, Forever 21]
-
A.
Forever 21
chosen
Forever 21 is a fast-fashion retail chain known for trendy, affordable clothing and accessories aimed primarily at young consumers.
-
B.
Ross Dress for Less
Ross Dress for Less is an American off-price retail chain offering discounted brand-name clothing, footwear, home décor, and accessories.
-
C.
Marshalls
Marshalls is a major American off-price department store chain known for selling brand-name clothing, home goods, and accessories at discounted prices.
-
D.
H&M
H&M is a global fast-fashion retail chain known for offering trendy clothing and accessories at affordable prices.
-
E.
H&M
H&M, in this context, refers to the historic Hudson and Manhattan Railroad, an early 20th-century rapid transit system that connected Manhattan with New Jersey and served as a predecessor to today’s PATH trains.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c475cda88190987d08f23caebdc1 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f0a7a890208190a902184e60194e1c |
completed | April 28, 2026, 12:27 p.m. |
Created at: April 16, 2026, 6:55 p.m.