Triple
T11845341
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NoMad |
E281759
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object | NoMad |
E281759
|
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: NoMad | Statement: [NoMad, shortName, NoMad]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: NoMad Context triple: [NoMad, shortName, NoMad]
-
A.
NoMad
chosen
NoMad is a trendy Manhattan neighborhood known for its historic architecture, upscale hotels, and vibrant dining and nightlife scene centered around Madison Square Park.
-
B.
NoMA
NoMA is the Norwegian Medicines Agency, the national authority responsible for regulating, approving, and monitoring medicines and medical devices in Norway.
-
C.
Hangover Square
Hangover Square is a dark psychological novel by Patrick Hamilton that follows a mentally unstable man in pre–World War II London as he becomes obsessed with a woman and descends toward violence.
-
D.
Brooklyn North
Brooklyn North is a policing command area of the New York City Police Department that encompasses several precincts in the northern part of Brooklyn.
-
E.
Speakeasy
Speakeasy is a stand-up comedy special by Malaysian comedian Ronny Chieng, known for its sharp observational humor and commentary on modern life.
- 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_69d6ab287ba48190a5178779fd19b9b7 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a65b5ff08190bb58361f6a6acdca |
completed | April 10, 2026, 7:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f167a876048190aeeeccebae9e46ad |
completed | April 29, 2026, 2:06 a.m. |
Created at: April 8, 2026, 9:43 p.m.