Triple
T2300505
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Texas Panhandle |
E51719
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object |
Borger
Borger is a small industrial city in the Texas Panhandle known historically for its oil and gas production.
|
E253844
|
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: Borger | Statement: [Texas Panhandle, hasCity, Borger]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Borger Context triple: [Texas Panhandle, hasCity, Borger]
-
A.
Boerne
Boerne is a small, historic town in south-central Texas known for its German heritage, charming downtown, and scenic Hill Country surroundings.
-
B.
Frohburg
Frohburg is a small town in the Free State of Saxony in eastern Germany, known for its historic architecture and rural surroundings.
-
C.
Kingsburg
Kingsburg is a small, historically Swedish-themed city in California’s San Joaquin Valley known for its agricultural community and distinctive Scandinavian character.
-
D.
Bordon
Bordon is a town in East Hampshire, England, historically known for its large army camp and military training facilities.
-
E.
Croston
Croston is a historic village in Lancashire, England, known for its picturesque rural setting, traditional architecture, and riverside location.
- 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: Borger Triple: [Texas Panhandle, hasCity, Borger]
Generated description
Borger is a small industrial city in the Texas Panhandle known historically for its oil and gas production.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Borger Target entity description: Borger is a small industrial city in the Texas Panhandle known historically for its oil and gas production.
-
A.
Boerne
Boerne is a small, historic town in south-central Texas known for its German heritage, charming downtown, and scenic Hill Country surroundings.
-
B.
Frohburg
Frohburg is a small town in the Free State of Saxony in eastern Germany, known for its historic architecture and rural surroundings.
-
C.
Kingsburg
Kingsburg is a small, historically Swedish-themed city in California’s San Joaquin Valley known for its agricultural community and distinctive Scandinavian character.
-
D.
Bordon
Bordon is a town in East Hampshire, England, historically known for its large army camp and military training facilities.
-
E.
Croston
Croston is a historic village in Lancashire, England, known for its picturesque rural setting, traditional architecture, and riverside location.
- 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_69a88b0a9f248190bcff941463d8f65a |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abc5edc1348190a4d84606b1310711 |
completed | March 7, 2026, 6:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae7f2e338881908e09d19f469a59ce |
completed | March 9, 2026, 8:05 a.m. |
| NEDg | Description generation | batch_69ae7fd78ee48190990fc7b5034b662b |
completed | March 9, 2026, 8:07 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae80dadf208190913211329a40b4ee |
completed | March 9, 2026, 8:12 a.m. |
Created at: March 4, 2026, 7:49 p.m.