Triple
T1768221
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Huangshi |
E38812
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object |
Xialu District
Xialu District is an urban administrative district of the prefecture-level city of Huangshi in Hubei Province, China.
|
E235763
|
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: Xialu District | Statement: [Huangshi, hasSubdivision, Xialu District]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Xialu District Context triple: [Huangshi, hasSubdivision, Xialu District]
-
A.
Yuhua District
Yuhua District is an urban administrative district of Changsha, the capital city of Hunan Province in south-central China.
-
B.
Xicheng District
Xicheng District is a central urban district of Beijing, China, known for its historic sites, government institutions, and cultural landmarks.
-
C.
Beibei District
Beibei District is an urban district of Chongqing, China, known for its scenic landscapes, hot springs, and educational institutions.
-
D.
Tieshan District
Tieshan District is an urban administrative district of the prefecture-level city of Huangshi in Hubei Province, China, known for its industrial and mining activities.
-
E.
Maojian District
Maojian District is the central urban district and administrative seat of Shiyan, a prefecture-level city in Hubei Province, China.
- 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: Xialu District Triple: [Huangshi, hasSubdivision, Xialu District]
Generated description
Xialu District is an urban administrative district of the prefecture-level city of Huangshi in Hubei Province, China.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Xialu District Target entity description: Xialu District is an urban administrative district of the prefecture-level city of Huangshi in Hubei Province, China.
-
A.
Yuhua District
Yuhua District is an urban administrative district of Changsha, the capital city of Hunan Province in south-central China.
-
B.
Xicheng District
Xicheng District is a central urban district of Beijing, China, known for its historic sites, government institutions, and cultural landmarks.
-
C.
Beibei District
Beibei District is an urban district of Chongqing, China, known for its scenic landscapes, hot springs, and educational institutions.
-
D.
Tieshan District
Tieshan District is an urban administrative district of the prefecture-level city of Huangshi in Hubei Province, China, known for its industrial and mining activities.
-
E.
Maojian District
Maojian District is the central urban district and administrative seat of Shiyan, a prefecture-level city in Hubei Province, China.
- 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_69a8862e61708190af97b9838cc3f5de |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa648bb44c81909245fb7ee23cb132 |
completed | March 6, 2026, 5:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae516bbbf48190ae87ec3344da64d1 |
completed | March 9, 2026, 4:49 a.m. |
| NEDg | Description generation | batch_69ae5209ae40819095e02cafb8112a1f |
completed | March 9, 2026, 4:52 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae529375788190aead19ec0874f11e |
completed | March 9, 2026, 4:54 a.m. |
Created at: March 4, 2026, 7:31 p.m.