Triple
T23492608
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mexia, Texas |
E570716
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Lake Mexia |
—
|
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: Lake Mexia | Statement: [Mexia, Texas, locatedNear, Lake Mexia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lake Mexia Context triple: [Mexia, Texas, locatedNear, Lake Mexia]
-
A.
Lake Mexia
chosen
Lake Mexia is a man-made reservoir in central Texas known for fishing, boating, and outdoor recreation.
-
B.
Lake Brownwood
Lake Brownwood is a reservoir in central Texas known for fishing, boating, and outdoor recreation, supported by the surrounding Lake Brownwood State Park.
-
C.
Sacapulas
Sacapulas is a municipality in Guatemala known for its traditional Maya Kʼicheʼ culture and distinctive salt production.
-
D.
Carrizo Springs
Carrizo Springs is a small city in Dimmit County, Texas, known as an agricultural and ranching hub in the South Texas region.
-
E.
Lake Ellis
Lake Ellis is a scenic high-altitude lake on the slopes of Mount Kenya, popular as a camping and rest spot along the Chogoria trekking route.
- 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_69e245b0b01481908f636939bedd804c |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a7dd56408190b459077e433ed1c3 |
completed | April 29, 2026, 6:40 a.m. |
Created at: April 17, 2026, 6:05 p.m.