Triple
T20599790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Otto-Werner Mueller |
E506142
|
entity |
| Predicate | residence |
P75
|
FINISHED |
| Object | New Haven |
—
|
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: New Haven | Statement: [Otto-Werner Mueller, residence, New Haven]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: New Haven Context triple: [Otto-Werner Mueller, residence, New Haven]
-
A.
New Haven
New Haven is a small city in central Kentucky known for its historic railroad heritage and proximity to the Kentucky Railway Museum.
-
B.
New Haven, Connecticut
chosen
New Haven, Connecticut is a historic coastal city in southern New England best known as the home of Yale University and a major center of education, culture, and research.
-
C.
Hartford
Hartford is the capital city of Connecticut and a historic center of insurance, government, and culture in the northeastern United States.
-
D.
Hartford
Hartford is a small city in eastern South Dakota that functions as a suburban community within the greater Sioux Falls metropolitan area.
-
E.
West Haven
West Haven is a coastal city in southern Connecticut known for its public beaches and shoreline along Long Island Sound.
- 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_69e0b4ba6ae88190af871e1f9522c704 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6aa1ef9ac8190b05e23c149529cb9 |
completed | April 20, 2026, 10:35 p.m. |
Created at: April 16, 2026, 11:40 a.m.