Triple
T20033502
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Erie Cemetery |
E497197
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Erie |
—
|
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: Erie | Statement: [Erie Cemetery, hasCity, Erie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Erie Context triple: [Erie Cemetery, hasCity, Erie]
-
A.
Erie
Erie is a small village in northwestern Illinois known for its rural character and close-knit community.
-
B.
Erie
Erie was one of the individual nuclear test shots conducted during the United States' Operation Redwing series of atmospheric nuclear weapons tests in 1956.
-
C.
Erie
chosen
Erie is a city in northwestern Pennsylvania on the shores of Lake Erie, known as a regional industrial and shipping center.
-
D.
Erie
Erie is a small town in Colorado known for its suburban residential character, proximity to both Denver and Boulder, and views of the nearby Rocky Mountains.
-
E.
Lake Ashtabula
Lake Ashtabula is a man-made reservoir in eastern North Dakota known for flood control, water supply, and recreational activities such as fishing and boating.
- 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_69da627278c88190babe4297a9df1236 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e662e6a7e481908069c1de2b3f94e0 |
completed | April 20, 2026, 5:31 p.m. |
Created at: April 11, 2026, 3:36 p.m.