Triple
T8412237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King's Road |
E198651
|
entity |
| Predicate | runsThrough |
P416
|
FINISHED |
| Object | Chelsea |
E525477
|
NE FINISHED |
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: Chelsea | Statement: [King's Road, runsThrough, Chelsea]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chelsea Context triple: [King's Road, runsThrough, Chelsea]
-
A.
Chelsea
Chelsea is a small, densely populated city in Massachusetts located just across the Mystic River from downtown Boston.
-
B.
Chelsea
Chelsea is a neighborhood on Manhattan’s West Side in New York City, known for its art galleries, nightlife, and historic architecture.
-
C.
Chelsea
Chelsea is a small municipality in western Quebec, Canada, known for its scenic natural surroundings and proximity to Gatineau Park.
-
D.
Chelsea
chosen
Chelsea is an affluent district in West London known for its upscale residential streets, fashionable boutiques, and cultural landmarks along the River Thames.
-
E.
Chelsea
Chelsea is a feminine given name of Old English origin that became widely popular in English-speaking countries in the late 20th century.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca831201b481909e137936ef99ff11 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cb83e0341c819080506e696131671e |
completed | March 31, 2026, 8:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce1cc9be088190b2b51281bc2f71bf |
completed | April 2, 2026, 7:37 a.m. |
Created at: March 30, 2026, 6:05 p.m.