Triple
T3111109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gary Snyder |
E64952
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Gary |
E38130
|
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: Gary | Statement: [Gary Snyder, givenName, Gary]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gary Context triple: [Gary Snyder, givenName, Gary]
-
A.
Gary
chosen
Gary is an industrial city in northwest Indiana, historically known for its steel production and location within the American Rust Belt.
-
B.
Gary
Gary is a small town in McDowell County, West Virginia, historically known as a coal mining community.
-
C.
Guy
Guy is a masculine given name of French origin that has been widely used in English-speaking countries.
-
D.
Guy
Guy is an influential American R&B group, central to the development of the new jack swing sound in the late 1980s and early 1990s.
-
E.
Greg
Greg is a male given name commonly used in English-speaking countries, often as a short form of Gregory.
- 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_69ad857eeaf48190b34ebfdaa7a264cf |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada43954f0819096a96331bf3c53a8 |
completed | March 8, 2026, 4:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b20f5cfc7c8190b867794c0e9a271e |
completed | March 12, 2026, 12:57 a.m. |
Created at: March 8, 2026, 3:04 p.m.