Triple
T14555943
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | City Tech |
E341541
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object | City Tech |
E341541
|
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: City Tech | Statement: [City Tech, shortName, City Tech]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: City Tech Context triple: [City Tech, shortName, City Tech]
-
A.
City Tech
chosen
City Tech is a public college in Brooklyn, New York, specializing in technology, engineering, and professional studies as part of the City University of New York (CUNY) system.
-
B.
Tech City
Tech City is a major technology startup and innovation hub centered around East London’s Silicon Roundabout.
-
C.
Citylabs
Citylabs is a major life sciences and biomedical innovation hub located within Manchester’s Corridor innovation district, housing research, healthcare, and technology organizations.
-
D.
Digital Cities
Digital Cities is a thematic area focused on using digital technologies and innovation to improve urban life, infrastructure, and city services.
-
E.
Cityscape
Cityscape is a 1987 jazz album featuring saxophonist Michael Brecker and composer-arranger Claus Ogerman, noted for its lush orchestral arrangements and atmospheric, cinematic sound.
- 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_69d822db9c8481908213ceb39585f792 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb2f1490881908673f429e5288c86 |
completed | April 14, 2026, 9:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd8abde0308190819da6867e703ea7 |
completed | May 8, 2026, 7:03 a.m. |
Created at: April 10, 2026, 1:23 a.m.