Triple
T22970828
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Town of Mono |
E571180
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Mono Centre
Mono Centre is a small rural community within the Town of Mono in Ontario, Canada, known for its scenic countryside and proximity to conservation areas.
|
E1563192
|
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: Mono Centre | Statement: [Town of Mono, contains, Mono Centre]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mono Centre Context triple: [Town of Mono, contains, Mono Centre]
-
A.
Centrum
Centrum is the historic city center district of Amsterdam, known for its canals, landmarks, and bustling markets.
-
B.
Centrum
Centrum is the central urban district and main commercial area of the Dutch city of Meppel.
-
C.
Centrum
Centrum is the central district and main urban core of the Dutch municipality of Ridderkerk.
-
D.
Magnocentro
Magnocentro is a major commercial and residential district in the municipality of Huixquilucan, in the State of Mexico, known for its shopping centers, offices, and high-rise housing developments.
-
E.
CentrO shopping center
CentrO shopping center is a large, modern retail and leisure complex in Oberhausen, Germany, known as one of the biggest shopping and entertainment centers in Europe.
- 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: Mono Centre Triple: [Town of Mono, contains, Mono Centre]
Generated description
Mono Centre is a small rural community within the Town of Mono in Ontario, Canada, known for its scenic countryside and proximity to conservation areas.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mono Centre Target entity description: Mono Centre is a small rural community within the Town of Mono in Ontario, Canada, known for its scenic countryside and proximity to conservation areas.
-
A.
Centrum
Centrum is the historic city center district of Amsterdam, known for its canals, landmarks, and bustling markets.
-
B.
Centrum
Centrum is the central urban district and main commercial area of the Dutch city of Meppel.
-
C.
Centrum
Centrum is the central district and main urban core of the Dutch municipality of Ridderkerk.
-
D.
Magnocentro
Magnocentro is a major commercial and residential district in the municipality of Huixquilucan, in the State of Mexico, known for its shopping centers, offices, and high-rise housing developments.
-
E.
CentrO shopping center
CentrO shopping center is a large, modern retail and leisure complex in Oberhausen, Germany, known as one of the biggest shopping and entertainment centers in Europe.
- 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_69e245b2c6548190a0e4c7f2f7df2d48 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1823272c4819083e4653d231facec |
completed | April 29, 2026, 3:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0bca28333c8190b517c2f4755e2e38 |
completed | May 19, 2026, 2:25 a.m. |
| NEDg | Description generation | batch_6a0bcacba35881909ee124b27afc9df4 |
completed | May 19, 2026, 2:28 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0bcba855d4819081d61e217b3747b0 |
completed | May 19, 2026, 2:32 a.m. |
Created at: April 17, 2026, 3:48 p.m.