Triple
T12523089
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maldon District |
E299366
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Tillingham
Tillingham is a small rural village and civil parish in the Maldon District of Essex, England, known for its historic church and traditional English countryside setting.
|
E986636
|
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: Tillingham | Statement: [Maldon District, contains, Tillingham]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tillingham Context triple: [Maldon District, contains, Tillingham]
-
A.
Tilton
Tilton is a locality in the United Kingdom notable for lending its name to the territorial designation of the peerage title Baron Keynes of Tilton.
-
B.
Tuddenham
Tuddenham is a village and civil parish located in the county of Suffolk in eastern England.
-
C.
Farlington
Farlington is a small rural village in North Yorkshire, England, situated near the River Foss and known for its historic parish church and agricultural surroundings.
-
D.
Farlington
Farlington is a residential suburb in the northern part of Portsmouth, England, known for its coastal location and access to major transport routes.
-
E.
Brimley
Brimley is a surname most notably associated with American actor Wilford Brimley, known for his roles in film, television, and commercials.
- 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: Tillingham Triple: [Maldon District, contains, Tillingham]
Generated description
Tillingham is a small rural village and civil parish in the Maldon District of Essex, England, known for its historic church and traditional English countryside setting.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tillingham Target entity description: Tillingham is a small rural village and civil parish in the Maldon District of Essex, England, known for its historic church and traditional English countryside setting.
-
A.
Tilton
Tilton is a locality in the United Kingdom notable for lending its name to the territorial designation of the peerage title Baron Keynes of Tilton.
-
B.
Tuddenham
Tuddenham is a village and civil parish located in the county of Suffolk in eastern England.
-
C.
Farlington
Farlington is a small rural village in North Yorkshire, England, situated near the River Foss and known for its historic parish church and agricultural surroundings.
-
D.
Farlington
Farlington is a residential suburb in the northern part of Portsmouth, England, known for its coastal location and access to major transport routes.
-
E.
Brimley
Brimley is a surname most notably associated with American actor Wilford Brimley, known for his roles in film, television, and commercials.
- 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_69d6ada5cdd48190860d9ce30aff69be |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d9545c2aa081908e8a5a94d30e23eb |
completed | April 10, 2026, 7:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f64bc159c88190835fea5c0d9ee799 |
completed | May 2, 2026, 7:08 p.m. |
| NEDg | Description generation | batch_69f64def9a6081908c3048f948829051 |
completed | May 2, 2026, 7:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f64ea1719c8190b91ffaab60db25ad |
completed | May 2, 2026, 7:21 p.m. |
Created at: April 8, 2026, 9:57 p.m.