Triple
T892954
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pittsburgh, Pennsylvania |
E19280
|
entity |
| Predicate | hasMayor |
P185
|
FINISHED |
| Object |
Ed Gainey
Ed Gainey is an American politician who became the first Black mayor of Pittsburgh, Pennsylvania.
|
E115696
|
NE FINISHED |
How this triple was built (4 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: Ed Gainey | Statement: [Pittsburgh, Pennsylvania, hasMayor, Ed Gainey]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ed Gainey Context triple: [Pittsburgh, Pennsylvania, hasMayor, Ed Gainey]
-
A.
Kevin O'Connor
Kevin O'Connor is an American entrepreneur best known as the co-founder and former CEO of the online advertising company DoubleClick.
-
B.
Jonathan Corwin
Jonathan Corwin was a 17th-century Massachusetts magistrate best known as one of the judges who presided over the Salem witch trials.
-
C.
Gerry Connolly
Gerry Connolly is a Democratic U.S. Congressman from Northern Virginia known for his work on government oversight, federal workforce issues, and foreign affairs.
-
D.
Mike Dunleavy
Mike Dunleavy is an American Republican politician and former educator who serves as the governor of Alaska.
-
E.
Mike Sullivan
Mike Sullivan is an American professional ice hockey coach best known for leading the Pittsburgh Penguins to multiple Stanley Cup championships.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Ed Gainey Triple: [Pittsburgh, Pennsylvania, hasMayor, Ed Gainey]
Generated description
Ed Gainey is an American politician who became the first Black mayor of Pittsburgh, Pennsylvania.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ed Gainey Target entity description: Ed Gainey is an American politician who became the first Black mayor of Pittsburgh, Pennsylvania.
-
A.
Kevin O'Connor
Kevin O'Connor is an American entrepreneur best known as the co-founder and former CEO of the online advertising company DoubleClick.
-
B.
Jonathan Corwin
Jonathan Corwin was a 17th-century Massachusetts magistrate best known as one of the judges who presided over the Salem witch trials.
-
C.
Gerry Connolly
Gerry Connolly is a Democratic U.S. Congressman from Northern Virginia known for his work on government oversight, federal workforce issues, and foreign affairs.
-
D.
Mike Dunleavy
Mike Dunleavy is an American Republican politician and former educator who serves as the governor of Alaska.
-
E.
Mike Sullivan
Mike Sullivan is an American professional ice hockey coach best known for leading the Pittsburgh Penguins to multiple Stanley Cup championships.
- F. None of above. chosen
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_69a4939d37188190848be3d426ebc9ae |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ad0304b081908d4c92bb2beadb81 |
completed | March 1, 2026, 9:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac1cd167188190aa05992376553550 |
completed | March 7, 2026, 12:40 p.m. |
| NEDg | Description generation | batch_69ac1d724cc081908296855b3caa5a5f |
completed | March 7, 2026, 12:43 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac1e04dc6c8190bcf9c4ffacc78aef |
completed | March 7, 2026, 12:45 p.m. |
Created at: March 1, 2026, 7:39 p.m.