Triple
T19452822
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suzanne Warren |
E486655
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Warren |
—
|
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: Warren | Statement: [Suzanne Warren, familyName, Warren]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Warren Context triple: [Suzanne Warren, familyName, Warren]
-
A.
Warren
Warren is the given name of Warren Buffett, the renowned American investor and longtime CEO of Berkshire Hathaway.
-
B.
Warren
chosen
Warren is a common English surname borne by numerous notable figures in politics, law, entertainment, and other fields.
-
C.
Warren
Warren is a large suburban city in southeast Michigan known for its extensive automotive and defense manufacturing industries.
-
D.
Warren
Warren is a small city in northern Pennsylvania known for its historic downtown and location along the Allegheny River.
-
E.
Warren
Warren is a central character in Robert Frost's narrative poem "The Death of the Hired Man," depicted as a New England farmer whose conflicted sense of duty and forgiveness shapes the story's moral tension.
- 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_69d8e8d86d608190bd199a98d0297f27 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6339407a08190a3e0213bfbb4df3d |
completed | April 20, 2026, 2:09 p.m. |
Created at: April 10, 2026, 1:38 p.m.