Triple
T14581900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daniel Lyons |
E342212
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Lyons |
E661925
|
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: Lyons | Statement: [Daniel Lyons, familyName, Lyons]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lyons Context triple: [Daniel Lyons, familyName, Lyons]
-
A.
Lyons
Lyons is a small city in southeastern Georgia, United States, known as the administrative and commercial hub of Toombs County.
-
B.
Lyons
Lyons is a small town in northern Colorado known as a gateway to the Rocky Mountains and for its vibrant music and arts scene.
-
C.
Lyons
Lyons is a sports team or athletic program associated with Wheaton College, commonly referred to by this shortened name.
-
D.
Lyons
chosen
Lyons is a common English and Irish surname borne by numerous notable individuals across sports, politics, arts, and other fields.
-
E.
Lyon
Lyon is a major city in east-central France known for its historical and architectural landmarks, gastronomy, and role as a key economic and cultural center.
- 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_69d822ddc0f081909cd8163c7de298cd |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb41e71748190a1deacc819dd26d3 |
completed | April 14, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fef885b07c8190af5e33303af9fbea |
completed | May 9, 2026, 9:04 a.m. |
Created at: April 10, 2026, 1:24 a.m.