Triple
T23640602
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central Railroad of New Jersey |
E583877
|
entity |
| Predicate | notableFacility |
P105
|
FINISHED |
| Object |
Bayonne, New Jersey yards
The Bayonne, New Jersey yards were a major rail yard complex in Bayonne that served as an important freight handling and classification hub for the Central Railroad of New Jersey.
|
E1594171
|
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: Bayonne, New Jersey yards | Statement: [Central Railroad of New Jersey, notableFacility, Bayonne, New Jersey yards]
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: Bayonne, New Jersey yards Triple: [Central Railroad of New Jersey, notableFacility, Bayonne, New Jersey yards]
Generated description
The Bayonne, New Jersey yards were a major rail yard complex in Bayonne that served as an important freight handling and classification hub for the Central Railroad of New Jersey.
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_69e248fe1c2c8190ac914d2442ff3d26 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b2808d888190a2198f5efd25f2df |
completed | April 29, 2026, 7:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0f45a6c55881908b4e49da244417cc |
completed | May 21, 2026, 5:49 p.m. |
| NEDg | Description generation | batch_6a0f47d607188190974666bddb39c7cf |
completed | May 21, 2026, 5:58 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0f4850ea448190a35ec999fe473262 |
completed | May 21, 2026, 6 p.m. |
Created at: April 17, 2026, 6:48 p.m.