Triple
T9927813
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BAM Fisher |
E187965
|
entity |
| Predicate | city |
P40
|
FINISHED |
| Object | Brooklyn |
E5446
|
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: Brooklyn | Statement: [BAM Fisher, city, Brooklyn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brooklyn Context triple: [BAM Fisher, city, Brooklyn]
-
A.
Brooklyn
chosen
Brooklyn is a populous and culturally diverse borough of New York City known for its distinct neighborhoods, arts scene, and iconic landmarks like the Brooklyn Bridge.
-
B.
Brooklyn
Brooklyn is a small inner-ring suburb of Cleveland located in Cuyahoga County, Ohio.
-
C.
Brooklyn
Brooklyn is a residential suburb within the Milnerton area of Cape Town, South Africa.
-
D.
Brooklyn
Brooklyn is a small city in Poweshiek County, Iowa, known for its collection of flags from around the world and its nickname "Community of Flags."
-
E.
Brooklyn
Brooklyn is a historic, primarily residential neighborhood in inner southeast Portland, Oregon, known for its close-in location, community feel, and mix of older homes and light industrial areas.
- 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_69ca82b22a688190b52c75bd48429c10 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cdb59d7ad08190982a1584547190bd |
completed | April 2, 2026, 12:17 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6a79eb5c08190ae75797556bc0943 |
completed | April 8, 2026, 7:08 p.m. |
Created at: March 30, 2026, 8:43 p.m.