Triple
T13300179
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Town of Niskayuna |
E316789
|
entity |
| Predicate | nearbyCity |
P350
|
FINISHED |
| Object | Albany, New York |
E5470
|
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: Albany, New York | Statement: [Town of Niskayuna, nearbyCity, Albany, New York]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Albany, New York Context triple: [Town of Niskayuna, nearbyCity, Albany, New York]
-
A.
Albany
chosen
Albany is the capital city of the U.S. state of New York, known as a historic political and cultural center in the northeastern United States.
-
B.
Albany
Albany is a coastal city in the Great Southern region of Western Australia, known for its natural harbors, historic whaling station, and role as a departure point for ANZAC troops in World War I.
-
C.
Albany
Albany is a suburb on Auckland’s North Shore in New Zealand, known for its rapid development, shopping centers, and proximity to major sports and educational facilities.
-
D.
Albany
Albany is a small village located in Athens County in southeastern Ohio, United States.
-
E.
Albany
Albany is a city in southwestern Georgia that serves as a regional hub for commerce, transportation, and culture.
- 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_69d806b40ab4819094adf6c374f4811a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d990a43ed88190a8dbbbd7d6d62dc4 |
completed | April 11, 2026, 12:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7266a316c81908361acc75581f211 |
completed | May 3, 2026, 10:41 a.m. |
Created at: April 9, 2026, 9:28 p.m.