Triple
T37448925
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | James Zadroga 9/11 Health and Compensation Act of 2010 |
E930626
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object |
James Zadroga
James Zadroga was a New York City police officer whose death from respiratory illness linked to his work at Ground Zero after the September 11 attacks led to landmark federal legislation providing health care and compensation to 9/11 responders and survivors.
|
E2226355
|
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: James Zadroga | Statement: [James Zadroga 9/11 Health and Compensation Act of 2010, namedAfter, James Zadroga]
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: James Zadroga Triple: [James Zadroga 9/11 Health and Compensation Act of 2010, namedAfter, James Zadroga]
Generated description
James Zadroga was a New York City police officer whose death from respiratory illness linked to his work at Ground Zero after the September 11 attacks led to landmark federal legislation providing health care and compensation to 9/11 responders and survivors.
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_69f76ec0b9488190b7a4fae632bd1d2f |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fb8e06269481909c4516b33fc10b05 |
completed | May 6, 2026, 6:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a408261996481909d3d2c48efea1451 |
completed | June 28, 2026, 2:09 a.m. |
| NEDg | Description generation | batch_6a4082d703748190b0d609d52adca94f |
completed | June 28, 2026, 2:11 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a40834942708190bd8bd3faa7a8f2c2 |
completed | June 28, 2026, 2:13 a.m. |
Created at: May 3, 2026, 4:17 p.m.