Triple
T14957192
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gimbels |
E372961
|
entity |
| Predicate | operatedIn |
P40
|
FINISHED |
| Object | Connecticut |
E10549
|
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: Connecticut | Statement: [Gimbels, operatedIn, Connecticut]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Connecticut Context triple: [Gimbels, operatedIn, Connecticut]
-
A.
Connecticut
chosen
Connecticut is a small New England state in the northeastern United States known for its colonial history, affluent suburbs, and role as a financial and educational hub.
-
B.
D. Conn.
D. Conn. is the standard legal abbreviation for the United States District Court for the District of Connecticut, a federal trial court within the Second Circuit.
-
C.
Rhoda Island
Rhoda Island is a Nile island in central Cairo, Egypt, known for its historic palaces, gardens, and cultural landmarks.
-
D.
Georgia, Vermont
Georgia, Vermont is a small rural town in northwestern Vermont known for its agricultural landscape and proximity to Lake Champlain.
-
E.
Vermont
Vermont is a small, rural New England state in the northeastern United States, known for its Green Mountains, maple syrup production, and picturesque towns.
- 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_69d85cca979481908747d2a81eba1cea |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6cc73848190ac181782b20dc838 |
completed | April 15, 2026, 12:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fea5a8b3708190be7c35a05fd08a52 |
completed | May 9, 2026, 3:10 a.m. |
Created at: April 10, 2026, 2:40 a.m.