Triple
T9597173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Big Bend National Park |
E231560
|
entity |
| Predicate | locatedInCounty |
P40
|
FINISHED |
| Object |
Brewster County
Brewster County is a vast, sparsely populated county in West Texas known for encompassing much of the Big Bend region along the Rio Grande.
|
E907333
|
NE FINISHED |
How this triple was built (4 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: Brewster County | Statement: [Big Bend National Park, locatedInCounty, Brewster County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brewster County Context triple: [Big Bend National Park, locatedInCounty, Brewster County]
-
A.
Reeves County
Reeves County is a sparsely populated county in western Texas known for its oil and gas production and desert landscapes.
-
B.
Gregg County
Gregg County is a county in East Texas best known for its county seat, Longview, and its role in the region’s oil and gas industry.
-
C.
McLennan County
McLennan County is a county in central Texas best known for encompassing the city of Waco, home to Baylor University.
-
D.
Nolan County
Nolan County is a county in west-central Texas known for its wind energy production and county seat, Sweetwater.
-
E.
Kerr County
Kerr County is a rural county in central Texas known for its scenic Hill Country landscapes, outdoor recreation, and the county seat of Kerrville.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Brewster County Triple: [Big Bend National Park, locatedInCounty, Brewster County]
Generated description
Brewster County is a vast, sparsely populated county in West Texas known for encompassing much of the Big Bend region along the Rio Grande.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Brewster County Target entity description: Brewster County is a vast, sparsely populated county in West Texas known for encompassing much of the Big Bend region along the Rio Grande.
-
A.
Reeves County
Reeves County is a sparsely populated county in western Texas known for its oil and gas production and desert landscapes.
-
B.
Gregg County
Gregg County is a county in East Texas best known for its county seat, Longview, and its role in the region’s oil and gas industry.
-
C.
McLennan County
McLennan County is a county in central Texas best known for encompassing the city of Waco, home to Baylor University.
-
D.
Nolan County
Nolan County is a county in west-central Texas known for its wind energy production and county seat, Sweetwater.
-
E.
Kerr County
Kerr County is a rural county in central Texas known for its scenic Hill Country landscapes, outdoor recreation, and the county seat of Kerrville.
- F. None of above. chosen
Provenance (5 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_69ca8482884481908eccdfdf64d6fbf7 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9a34f5408190ba72ba8311eb259c |
completed | April 1, 2026, 10:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4415b7f848190a9fc8b08824f0b9b |
completed | April 19, 2026, 2:43 a.m. |
| NEDg | Description generation | batch_69e448f697a88190ae711c72ae0c0c3b |
completed | April 19, 2026, 3:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e4510dc55081908f89aab15726b2a8 |
completed | April 19, 2026, 3:50 a.m. |
Created at: March 30, 2026, 8:07 p.m.