Triple
T22231543
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Soho Square |
E549476
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Soho district |
—
|
NE NERFINISHED |
How this triple was built (2 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: Soho district | Statement: [Soho Square, namedAfter, Soho district]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Soho district Context triple: [Soho Square, namedAfter, Soho district]
-
A.
Soho
Soho is an inner-city district of Birmingham, England, historically known for its industrial heritage and diverse local community.
-
B.
Soho
Soho is a vibrant dining, nightlife, and entertainment district in Hong Kong known for its steep streets, trendy bars, and international restaurants.
-
C.
Soho
chosen
Soho is a vibrant central London district famed for its nightlife, entertainment venues, and diverse cultural scene.
-
D.
Kensington Market
Kensington Market is a vibrant, historically multicultural neighborhood in Toronto known for its eclectic shops, diverse food offerings, and bohemian street culture.
-
E.
Temple Bar district
Temple Bar district is a historic and lively cultural quarter in central Dublin known for its cobbled streets, pubs, nightlife, and arts venues.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e4102b881909cf47d3768e25c19 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12bf3de648190986a734f19643a8c |
completed | April 28, 2026, 9:51 p.m. |
Created at: April 16, 2026, 8:38 p.m.