Triple
T10694810
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Louisa Houghton Macy |
E252106
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | Macy's |
E78374
|
NE 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: Macy's | Statement: [Louisa Houghton Macy, associatedWith, Macy's]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Macy's Context triple: [Louisa Houghton Macy, associatedWith, Macy's]
-
A.
Macy's
chosen
Macy's is a major American department store chain known for its wide range of apparel, home goods, and its flagship store in New York City.
-
B.
Marshalls
Marshalls is a major American off-price department store chain known for selling brand-name clothing, home goods, and accessories at discounted prices.
-
C.
Nordstrom
Nordstrom is a leading American luxury department store chain known for its high-end fashion, quality customer service, and nationwide retail presence.
-
D.
Lord & Taylor
Lord & Taylor is a historic American department store chain known for its upscale fashion offerings and flagship presence on New York City's Fifth Avenue.
-
E.
J. C. Penney
J. C. Penney was an American businessman and entrepreneur best known as the founder of the JCPenney department store chain.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d6aa5bd7c08190a816e733b4045c23 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6fd39c3788190bb7cd0acf8b6efdd |
completed | April 9, 2026, 1:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d998cfeb748190bfff06534d83cf97 |
completed | April 11, 2026, 12:41 a.m. |
Created at: April 8, 2026, 9:11 p.m.