Triple
T21427824
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Martin Crimp |
E528606
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | The City |
—
|
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: The City | Statement: [Martin Crimp, notableWork, The City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The City Context triple: [Martin Crimp, notableWork, The City]
-
A.
The City
The City is a common nickname for Manhattan, the densely populated and iconic borough of New York City known for its skyscrapers, cultural landmarks, and role as a global financial and media hub.
-
B.
The City
The City is a 1919–1920 Cubist painting by Fernand Léger that depicts the dynamism and fragmentation of modern urban life through bold colors and geometric forms.
-
C.
The City
The City is a science fiction short story by Ray Bradbury that explores themes of revenge and the lingering consequences of war through the perspective of a sentient, vengeful metropolis.
-
D.
The City
chosen
The City is a work associated with Laura Wright, likely a creative piece such as a novel, play, or other artistic production.
-
E.
The City
"The City" is a modern dance work choreographed by influential German-American dancer and teacher Hanya Holm.
- 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_69e0c455f3688190810bc96365791b0f |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e8b3e63a54819089efea2f26b58107 |
completed | April 22, 2026, 11:41 a.m. |
Created at: April 16, 2026, 5:49 p.m.