Triple
T29810515
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Town of Poestenkill, New York |
E756947
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object |
Town of Berlin, New York
The Town of Berlin, New York, is a small rural community in eastern Rensselaer County within New York’s Capital District, known for its mountainous terrain and quiet, scenic character near the Vermont and Massachusetts borders.
|
E1887377
|
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: Town of Berlin, New York | Statement: [Town of Poestenkill, New York, borderedBy, Town of Berlin, New York]
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: Town of Berlin, New York Triple: [Town of Poestenkill, New York, borderedBy, Town of Berlin, New York]
Generated description
The Town of Berlin, New York, is a small rural community in eastern Rensselaer County within New York’s Capital District, known for its mountainous terrain and quiet, scenic character near the Vermont and Massachusetts borders.
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_69f2245584848190ad4cab1f07752ccb |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f6752de184819086c6665f614f71a6 |
completed | May 2, 2026, 10:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a26e5f17d408190a95e3747dd70b447 |
completed | June 8, 2026, 3:55 p.m. |
| NEDg | Description generation | batch_6a26e732f0e0819083339b975200cb17 |
completed | June 8, 2026, 4 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a26e809c3a88190bba9c39027ab587a |
completed | June 8, 2026, 4:04 p.m. |
Created at: April 29, 2026, 5:23 p.m.