Triple
T20000415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eve Kosofsky Sedgwick |
E494306
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Sedgwick |
—
|
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: Sedgwick | Statement: [Eve Kosofsky Sedgwick, familyName, Sedgwick]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sedgwick Context triple: [Eve Kosofsky Sedgwick, familyName, Sedgwick]
-
A.
Sedgwick
chosen
Sedgwick is an English-origin surname borne by various notable figures in fields such as acting, literature, and academia.
-
B.
Sedgwick
Sedgwick is a small village in Cumbria, England, known for its rural setting near Kendal and its historic canal and riverside scenery.
-
C.
Sedgwick
Sedgwick is a Chicago Transit Authority 'L' station serving the Brown Line in Chicago, Illinois.
-
D.
Sedgwick
Sedgwick is a small village in West Sussex, England, known for its rural character and proximity to the town of Horsham.
-
E.
Bridgeland
Bridgeland is a large, master-planned residential community in Cypress, Texas, known for its extensive amenities, green spaces, and family-oriented neighborhoods.
- 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_69da626b2d748190886981ea90c8b2ea |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e661a15f308190a99ac3205f948acb |
completed | April 20, 2026, 5:25 p.m. |
Created at: April 11, 2026, 3:32 p.m.