Triple
T2218041
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bloomsbury |
E48076
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Queen Square
Queen Square is a historic garden square in the Bloomsbury district of central London, known for its Georgian architecture and nearby medical and academic institutions.
|
E244006
|
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: Queen Square | Statement: [Bloomsbury, hasPart, Queen Square]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Queen Square Context triple: [Bloomsbury, hasPart, Queen Square]
-
A.
Queen Square
Queen Square is a historic public square located in the coastal city of Brunswick, Georgia.
-
B.
Queen’s Square
Queen’s Square is a residential neighborhood within Belize City, Belize.
-
C.
Trinity Square
Trinity Square is a historic public square in the City of London, known for its memorials and proximity to the Tower of London.
-
D.
Albert Square
Albert Square is a prominent public square in central Manchester, England, known for its Victorian architecture, civic monuments, and role as a focal point for events and gatherings.
-
E.
Waverley Square
Waverley Square is a commercial and transit-oriented neighborhood in Belmont, Massachusetts, known for its local shops and MBTA commuter rail station.
- 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: Queen Square Triple: [Bloomsbury, hasPart, Queen Square]
Generated description
Queen Square is a historic garden square in the Bloomsbury district of central London, known for its Georgian architecture and nearby medical and academic institutions.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Queen Square Target entity description: Queen Square is a historic garden square in the Bloomsbury district of central London, known for its Georgian architecture and nearby medical and academic institutions.
-
A.
Queen Square
Queen Square is a historic public square located in the coastal city of Brunswick, Georgia.
-
B.
Queen’s Square
Queen’s Square is a residential neighborhood within Belize City, Belize.
-
C.
Trinity Square
Trinity Square is a historic public square in the City of London, known for its memorials and proximity to the Tower of London.
-
D.
Albert Square
Albert Square is a prominent public square in central Manchester, England, known for its Victorian architecture, civic monuments, and role as a focal point for events and gatherings.
-
E.
Waverley Square
Waverley Square is a commercial and transit-oriented neighborhood in Belmont, Massachusetts, known for its local shops and MBTA commuter rail station.
- 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_69a88aa1ee708190862c8c378c41e9eb |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc010bd4c8190ace293b37eac1de5 |
completed | March 7, 2026, 6:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae655b369c8190a5d12b87401534d7 |
completed | March 9, 2026, 6:14 a.m. |
| NEDg | Description generation | batch_69ae65d419048190ad723d21ab7f1cab |
completed | March 9, 2026, 6:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae666e71908190b50be2cac5bdfa28 |
completed | March 9, 2026, 6:19 a.m. |
Created at: March 4, 2026, 7:46 p.m.