Triple
T1168218
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Hick from French Lick |
E24848
|
entity |
| Predicate | hasWord |
P35
|
FINISHED |
| Object | French Lick |
E25680
|
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: French Lick | Statement: [The Hick from French Lick, hasWord, French Lick]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: French Lick Context triple: [The Hick from French Lick, hasWord, French Lick]
-
A.
French Lick, Indiana, United States
chosen
French Lick, Indiana, United States, is a small Midwestern town best known as the hometown of basketball legend Larry Bird and for its historic resort and mineral springs.
-
B.
Peacock Springs
Peacock Springs is a renowned freshwater spring and underwater cave system in northern Florida, popular with divers and nature enthusiasts.
-
C.
Otsego
Otsego is a small city in southwestern Michigan known historically for its paper mills and location along the Kalamazoo River.
-
D.
Lakeside
Lakeside is a small settlement in England’s Lake District, known as a lakeside stop and tourist base on the southern shore of Windermere.
-
E.
Lakeside
Lakeside is an upscale seafood restaurant at the Wynn Las Vegas known for its lakefront views and fine dining experience.
- 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_69a494082a7c819095004f423f294a64 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bccef84481908864e819884af86c |
completed | March 1, 2026, 10:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac6f17aa608190920b7df62b8dd903 |
completed | March 7, 2026, 6:31 p.m. |
Created at: March 1, 2026, 7:45 p.m.