Triple
T12729170
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liupanshui |
E304185
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object |
Pan County
Pan County is an administrative county under the jurisdiction of Liupanshui City in Guizhou Province, southwestern China.
|
E1015535
|
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: Pan County | Statement: [Liupanshui, hasSubdivision, Pan County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pan County Context triple: [Liupanshui, hasSubdivision, Pan County]
-
A.
Pulaski County
Pulaski County is a rural county in central Georgia known for its agricultural landscape and the city of Hawkinsville as its county seat.
-
B.
Pulaski County
Pulaski County is a county in central Arkansas that includes the state capital, Little Rock, and serves as a major governmental, economic, and cultural hub of the region.
-
C.
Mills County
Mills County is a rural county in the southwestern part of the U.S. state of Iowa, known for its agricultural landscape and small communities.
-
D.
Phillips County
Phillips County is a rural county in the northeastern region of Colorado known for its agricultural landscape and small communities.
-
E.
Hill County
Hill County is a rural county in central Texas known for its small towns, agricultural economy, and location between Waco and the Dallas–Fort Worth area.
- 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: Pan County Triple: [Liupanshui, hasSubdivision, Pan County]
Generated description
Pan County is an administrative county under the jurisdiction of Liupanshui City in Guizhou Province, southwestern China.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Pan County Target entity description: Pan County is an administrative county under the jurisdiction of Liupanshui City in Guizhou Province, southwestern China.
-
A.
Pulaski County
Pulaski County is a county in central Arkansas that includes the state capital, Little Rock, and serves as a major governmental, economic, and cultural hub of the region.
-
B.
Pulaski County
Pulaski County is a rural county in central Georgia known for its agricultural landscape and the city of Hawkinsville as its county seat.
-
C.
Mills County
Mills County is a rural county in the southwestern part of the U.S. state of Iowa, known for its agricultural landscape and small communities.
-
D.
Phillips County
Phillips County is a rural county in the northeastern region of Colorado known for its agricultural landscape and small communities.
-
E.
Hill County
Hill County is a rural county in central Texas known for its small towns, agricultural economy, and location between Waco and the Dallas–Fort Worth area.
- 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_69d7bdf1426c8190a4402e1c4cdec33a |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d964172490819080cd022ff8290b6e |
completed | April 10, 2026, 8:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6c0dace788190bf2663984801f38c |
completed | May 3, 2026, 3:28 a.m. |
| NEDg | Description generation | batch_69f6c34532148190a0c609ff085e359c |
completed | May 3, 2026, 3:38 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6c3c6b240819099310f50cc7eabca |
completed | May 3, 2026, 3:40 a.m. |
Created at: April 9, 2026, 5:25 p.m.