Triple
T17860527
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Warren Street |
E446057
|
entity |
| Predicate | hasNearbyArea |
P4647
|
FINISHED |
| Object | Bloomsbury |
—
|
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: Bloomsbury | Statement: [Warren Street, hasNearbyArea, Bloomsbury]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bloomsbury Context triple: [Warren Street, hasNearbyArea, Bloomsbury]
-
A.
Bloomsbury
chosen
Bloomsbury is a central London district renowned for its literary heritage, academic institutions, and garden squares.
-
B.
Bloomsbury
Bloomsbury is a British independent publishing house best known for releasing the Harry Potter series and a wide range of literary and academic works.
-
C.
Camden House
Camden House is a teaching and administrative building that forms part of the University College Birmingham city-centre campus.
-
D.
Bodley Head
Bodley Head is a British publishing house known for its literary fiction, non-fiction, and classic works.
-
E.
Melbourne House
Melbourne House was a British video game publisher and developer best known for its influential 1980s home computer titles and licensed adaptations.
- 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_69d8b9f26f18819089c9e43250bee6ae |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4979013dc8190beb7718f0ba92bc3 |
completed | April 19, 2026, 8:51 a.m. |
Created at: April 10, 2026, 10:17 a.m.