Triple
T4033045
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Midtown |
E83758
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Garment District |
E73677
|
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: Garment District | Statement: [Midtown, contains, Garment District]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Garment District Context triple: [Midtown, contains, Garment District]
-
A.
Garment District
chosen
The Garment District is a New York City neighborhood renowned as the historic center of the American fashion and apparel industry, filled with showrooms, production facilities, and fashion-related businesses.
-
B.
Meatpacking District
The Meatpacking District is a trendy Manhattan neighborhood known for its cobblestone streets, high-end boutiques, nightlife, and the southern end of the High Line park.
-
C.
SoHo
SoHo is a fashionable Lower Manhattan neighborhood known for its cast-iron architecture, art galleries, and upscale boutiques.
-
D.
SoHo
SoHo is a vibrant commercial and entertainment district in Hong Kong known for its trendy restaurants, bars, and nightlife.
-
E.
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.
- 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_69aed92e29ac819080f7a98b594fec05 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb108fc0819080c8f41da2e558e0 |
completed | March 9, 2026, 4:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5563b6d8c8190862597ea39b56de1 |
completed | March 14, 2026, 12:36 p.m. |
Created at: March 9, 2026, 3:36 p.m.