Triple
T37350560
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pennsylvania Avenue, Brooklyn |
E927309
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object |
Seaview Avenue, Brooklyn
Seaview Avenue in Brooklyn is a major east–west thoroughfare in the borough’s southeastern neighborhoods, running through areas such as Canarsie and East New York.
|
E2228206
|
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: Seaview Avenue, Brooklyn | Statement: [Pennsylvania Avenue, Brooklyn, connectsTo, Seaview Avenue, Brooklyn]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Seaview Avenue, Brooklyn Triple: [Pennsylvania Avenue, Brooklyn, connectsTo, Seaview Avenue, Brooklyn]
Generated description
Seaview Avenue in Brooklyn is a major east–west thoroughfare in the borough’s southeastern neighborhoods, running through areas such as Canarsie and East New York.
Provenance (5 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_69f76eb5e034819088e53ab5b7909a68 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fb5bc062e8819098f3b5486eb754d1 |
completed | May 6, 2026, 3:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a408c20fd28819094bd0a2530fdaabc |
completed | June 28, 2026, 2:51 a.m. |
| NEDg | Description generation | batch_6a408d41efa48190a0d89da42e673c2b |
completed | June 28, 2026, 2:56 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a408dab83008190b966064e782ca385 |
completed | June 28, 2026, 2:57 a.m. |
Created at: May 3, 2026, 4:16 p.m.