Triple
T6104919
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lunan Water |
E136093
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object |
village of Lunan
The village of Lunan is a small Scottish coastal settlement known for its proximity to Lunan Bay and its scenic rural surroundings.
|
E568466
|
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: village of Lunan | Statement: [Lunan Water, locatedNear, village of Lunan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: village of Lunan Context triple: [Lunan Water, locatedNear, village of Lunan]
-
A.
Gucun Town
Gucun Town is a suburban township in Shanghai, China, known for its large Gucun Park and residential communities within Baoshan District.
-
B.
Mutianyu village
Mutianyu village is a small settlement in Huairou District, Beijing, best known as the gateway to the popular Mutianyu section of the Great Wall of China.
-
C.
Luodian Town
Luodian Town is a suburban town in Shanghai, China, known for its residential communities and local commerce within Baoshan District.
-
D.
Wulidian
Wulidian is a locality within Beijing’s Fengtai District, known primarily as a residential and commercial urban neighborhood.
-
E.
Huangcun
Huangcun is a town in Beijing, China, that serves as the administrative and commercial center of the city's southern Daxing District.
- 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: village of Lunan Triple: [Lunan Water, locatedNear, village of Lunan]
Generated description
The village of Lunan is a small Scottish coastal settlement known for its proximity to Lunan Bay and its scenic rural surroundings.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: village of Lunan Target entity description: The village of Lunan is a small Scottish coastal settlement known for its proximity to Lunan Bay and its scenic rural surroundings.
-
A.
Gucun Town
Gucun Town is a suburban township in Shanghai, China, known for its large Gucun Park and residential communities within Baoshan District.
-
B.
Mutianyu village
Mutianyu village is a small settlement in Huairou District, Beijing, best known as the gateway to the popular Mutianyu section of the Great Wall of China.
-
C.
Luodian Town
Luodian Town is a suburban town in Shanghai, China, known for its residential communities and local commerce within Baoshan District.
-
D.
Wulidian
Wulidian is a locality within Beijing’s Fengtai District, known primarily as a residential and commercial urban neighborhood.
-
E.
Huangcun
Huangcun is a town in Beijing, China, that serves as the administrative and commercial center of the city's southern Daxing District.
- 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_69c0087dee9881909e3655be88208c01 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c05b3f8e5481909e85a60aaf319f66 |
completed | March 22, 2026, 9:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c1255759f48190a6aadf33406dcb49 |
completed | March 23, 2026, 11:34 a.m. |
| NEDg | Description generation | batch_69c1275910108190a0a5f458a468c292 |
completed | March 23, 2026, 11:43 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c127b831d081909436a62e002d1fa5 |
completed | March 23, 2026, 11:44 a.m. |
Created at: March 22, 2026, 4:13 p.m.