Triple
T18287746
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Benjamin Webster |
E438026
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Webster |
—
|
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: Webster | Statement: [Benjamin Webster, familyName, Webster]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Webster Context triple: [Benjamin Webster, familyName, Webster]
-
A.
Webster
chosen
Webster is a common English surname most famously associated with American lexicographer Noah Webster, whose name is linked to influential early American dictionaries.
-
B.
Webster
Webster is a city in the Houston metropolitan area of Texas, known for its proximity to Clear Lake and the NASA Johnson Space Center.
-
C.
Merriam
Merriam is a surname most notably associated with American zoologist and ethnographer Clinton Hart Merriam.
-
D.
Merriam
Merriam is a small suburban city in Johnson County, Kansas, within the Kansas City metropolitan area.
-
E.
Webster’s Unabridged Dictionary
Webster’s Unabridged Dictionary is a comprehensive, authoritative American English dictionary renowned for its extensive word coverage and detailed definitions.
- 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_69d8b914530c8190b4474d862a2b2a1b |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e500faf62081908f16ebee0a195ba2 |
completed | April 19, 2026, 4:21 p.m. |
Created at: April 10, 2026, 10:35 a.m.