Triple
T5559579
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Florence Augusta Merriam Bailey |
E145731
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Merriam |
E144686
|
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: Merriam | Statement: [Florence Augusta Merriam Bailey, familyName, Merriam]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Merriam Context triple: [Florence Augusta Merriam Bailey, familyName, Merriam]
-
A.
Merriam
chosen
Merriam is a surname most notably associated with American zoologist and ethnographer Clinton Hart Merriam.
-
B.
Webster
Webster is a common English surname most famously associated with American lexicographer Noah Webster, whose name is linked to influential early American dictionaries.
-
C.
Merrill
Merrill is the wealth management and brokerage division of Bank of America, offering investment advice, financial planning, and related services to individual and institutional clients.
-
D.
Merrill
Merrill is a surname most notably associated with American actor Gary Merrill, known for his work in mid-20th-century film and television.
-
E.
Collins
Collins is a major aerospace and defense technology company known for providing advanced avionics and aircraft systems to commercial and military customers worldwide.
- 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_69c008fcaf788190bafa02a1917ee73b |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c020167afc8190b0c518907cd0d99b |
completed | March 22, 2026, 5 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c07d7658a481909e9e9b29df2b148e |
completed | March 22, 2026, 11:38 p.m. |
Created at: March 22, 2026, 3:36 p.m.