Triple
T13031203
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montreal Eaton’s store |
E326443
|
entity |
| Predicate | operatedBy |
P86
|
FINISHED |
| Object | Eaton’s |
E304545
|
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: Eaton’s | Statement: [Montreal Eaton’s store, operatedBy, Eaton’s]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eaton’s Context triple: [Montreal Eaton’s store, operatedBy, Eaton’s]
-
A.
Eaton’s
chosen
Eaton’s was a major Canadian department store chain that became a retail icon and helped shape downtown shopping districts across the country.
-
B.
Eaton
Eaton is a small town located within Madison County in the state of New York, United States.
-
C.
Eaton
Eaton is a surname most notably associated with American decathlete and Olympic gold medalist Ashton Eaton.
-
D.
Eaton
Eaton is the namesake of the Eaton Professor of the Science of Government at Harvard University, an endowed academic chair in political science and government studies.
-
E.
Eaton Ford
Eaton Ford is a residential area and former village in Cambridgeshire, England, situated on the western side of the River Great Ouse opposite the town of St Neots.
- 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_69d8076cc45c81908123123f43e69266 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97efe72348190b52fb4068f5fb829 |
completed | April 10, 2026, 10:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6cbcd25108190a6c4a129cde81534 |
completed | May 3, 2026, 4:15 a.m. |
Created at: April 9, 2026, 8:54 p.m.