Triple
T6488588
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ann Deever |
E146576
|
entity |
| Predicate | visits |
P60586
|
FINISHED |
| Object | Keller home |
E531519
|
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: Keller home | Statement: [Ann Deever, visits, Keller home]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Keller home Context triple: [Ann Deever, visits, Keller home]
-
A.
Keller family home
chosen
The Keller family home is the primary domestic setting in Arthur Miller’s play "All My Sons," where the tensions, secrets, and moral conflicts of the Keller family unfold.
-
B.
Keller backyard
The Keller backyard is the primary outdoor setting in Arthur Miller’s play "All My Sons," where much of the drama involving characters like Dr. Jim Bayliss unfolds.
-
C.
House of Kettler
The House of Kettler was a prominent Baltic German noble dynasty that ruled the Duchy of Courland and Semigallia in the early modern period.
-
D.
Kaisa House
Kaisa House is the main library building of the University of Helsinki, known for its modern architecture and role as a central hub for academic study and research.
-
E.
Pat House
Pat House is a technology executive best known as a co-founder of Siebel Systems, a pioneering customer relationship management (CRM) software company.
- 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_69c0090158c08190af0df9a2348d2d52 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c06a97fff88190b6f993c14df62649 |
completed | March 22, 2026, 10:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c653b792f48190b301cdc643db8ddf |
completed | March 27, 2026, 9:53 a.m. |
Created at: March 22, 2026, 4:52 p.m.