Triple
T15592287
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lamb County |
E374774
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object |
Sudan, Texas
Sudan, Texas is a small rural town in the Texas Panhandle known for its agricultural economy and close-knit community.
|
E1165385
|
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: Sudan, Texas | Statement: [Lamb County, hasTown, Sudan, Texas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sudan, Texas Context triple: [Lamb County, hasTown, Sudan, Texas]
-
A.
Turkey, Texas
Turkey, Texas is a small rural community in the Texas Panhandle best known as the hometown of Western swing music legend Bob Wills.
-
B.
Palestine, Texas
Palestine, Texas is a small East Texas city known for its historic downtown, dogwood blossoms, and role as a regional rail and commerce hub.
-
C.
Hannibal, Texas
Hannibal, Texas is a small rural unincorporated community located in Erath County in north-central Texas.
-
D.
Sanger, Texas
Sanger, Texas is a small city in Denton County known for its rural character and proximity to outdoor recreation at Ray Roberts Lake.
-
E.
Lampasas, Texas
Lampasas, Texas is a small central Texas city known for its historic downtown, mineral springs, and role as a regional hub along major north–south travel routes.
- 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: Sudan, Texas Triple: [Lamb County, hasTown, Sudan, Texas]
Generated description
Sudan, Texas is a small rural town in the Texas Panhandle known for its agricultural economy and close-knit community.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sudan, Texas Target entity description: Sudan, Texas is a small rural town in the Texas Panhandle known for its agricultural economy and close-knit community.
-
A.
Turkey, Texas
Turkey, Texas is a small rural community in the Texas Panhandle best known as the hometown of Western swing music legend Bob Wills.
-
B.
Palestine, Texas
Palestine, Texas is a small East Texas city known for its historic downtown, dogwood blossoms, and role as a regional rail and commerce hub.
-
C.
Hannibal, Texas
Hannibal, Texas is a small rural unincorporated community located in Erath County in north-central Texas.
-
D.
Sanger, Texas
Sanger, Texas is a small city in Denton County known for its rural character and proximity to outdoor recreation at Ray Roberts Lake.
-
E.
Lampasas, Texas
Lampasas, Texas is a small central Texas city known for its historic downtown, mineral springs, and role as a regional hub along major north–south travel routes.
- 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_69d85cce25008190b13b52745fbd719b |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e5e43d48190a8fd367f13f1c7e1 |
completed | April 16, 2026, 2:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff4c55fa248190b114a5b63560f87b |
completed | May 9, 2026, 3:01 p.m. |
| NEDg | Description generation | batch_69ff50020d748190be36f3c08df43e40 |
completed | May 9, 2026, 3:17 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff50a349688190ab7a18fa4460d86e |
completed | May 9, 2026, 3:20 p.m. |
Created at: April 10, 2026, 4:12 a.m.