Triple
T21505536
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Broken Kilometer |
E530588
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | SoHo, Manhattan |
—
|
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, Manhattan | Statement: [The Broken Kilometer, locatedIn, SoHo, Manhattan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SoHo, Manhattan Context triple: [The Broken Kilometer, locatedIn, SoHo, Manhattan]
-
A.
SoHo
chosen
SoHo is a fashionable Lower Manhattan neighborhood known for its cast-iron architecture, art galleries, and upscale boutiques.
-
B.
SoHo
SoHo is a vibrant commercial and entertainment district in Hong Kong known for its trendy restaurants, bars, and nightlife.
-
C.
NoHo, Manhattan
NoHo, Manhattan is a small, upscale neighborhood in Lower Manhattan known for its historic cast-iron architecture, trendy boutiques, and vibrant arts and dining scene.
-
D.
Flatiron District
The Flatiron District is a Manhattan neighborhood known for its iconic Flatiron Building, historic architecture, and role as a hub for tech companies and trendy dining.
-
E.
Leather District
The Leather District is a small historic neighborhood in Boston known for its 19th-century brick warehouse buildings and former leather industry.
- 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_69e0c45c81f08190a6b8bbb70a45aae7 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea7cb5588190a4473bbfe3f49cbb |
completed | April 23, 2026, 9:46 a.m. |
Created at: April 16, 2026, 6:24 p.m.