Triple
T3628071
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | McLennan County |
E76887
|
entity |
| Predicate | bordersOn |
P224
|
FINISHED |
| Object |
Falls County
Falls County is a rural county in central Texas known for its agricultural economy and small communities along the Brazos River.
|
E432401
|
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: Falls County | Statement: [McLennan County, bordersOn, Falls County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Falls County Context triple: [McLennan County, bordersOn, Falls County]
-
A.
Cottle County
Cottle County is a sparsely populated rural county in north-central Texas known for its ranching, agriculture, and small-town communities.
-
B.
Parmer County
Parmer County is a rural county in the western Texas Panhandle known for its agriculture-based economy and small, close-knit communities.
-
C.
Donley County
Donley County is a rural county in the Texas Panhandle known for its ranching heritage, small communities, and wide-open High Plains landscapes.
-
D.
Waller County
Waller County is a county in southeastern Texas that forms part of the greater Houston metropolitan region.
-
E.
Logan County
Logan County is a largely rural, coal-mining region in southern West Virginia known for its Appalachian landscape and history.
- 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: Falls County Triple: [McLennan County, bordersOn, Falls County]
Generated description
Falls County is a rural county in central Texas known for its agricultural economy and small communities along the Brazos River.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Falls County Target entity description: Falls County is a rural county in central Texas known for its agricultural economy and small communities along the Brazos River.
-
A.
Cottle County
Cottle County is a sparsely populated rural county in north-central Texas known for its ranching, agriculture, and small-town communities.
-
B.
Parmer County
Parmer County is a rural county in the western Texas Panhandle known for its agriculture-based economy and small, close-knit communities.
-
C.
Donley County
Donley County is a rural county in the Texas Panhandle known for its ranching heritage, small communities, and wide-open High Plains landscapes.
-
D.
Waller County
Waller County is a county in southeastern Texas that forms part of the greater Houston metropolitan region.
-
E.
Logan County
Logan County is a largely rural, coal-mining region in southern West Virginia known for its Appalachian landscape and history.
- 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_69ad85dc03948190b35b7189e4175bcc |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc2ddccc881909ae13dca3dd8a11d |
completed | March 8, 2026, 6:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5db5d2fcc8190818b79d873cebcf6 |
completed | March 14, 2026, 10:04 p.m. |
| NEDg | Description generation | batch_69b5dbe844e4819099dbd1ed65f262fb |
completed | March 14, 2026, 10:06 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5dc5a2b008190907150ada5714fac |
completed | March 14, 2026, 10:08 p.m. |
Created at: March 8, 2026, 3:23 p.m.