Triple
T3342394
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The District |
E70288
|
entity |
| Predicate | creator |
P184
|
FINISHED |
| Object |
Jack Maple
Jack Maple was an influential New York City transit police officer and crime strategist best known for co-developing the CompStat system that transformed modern policing.
|
E349973
|
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: Jack Maple | Statement: [The District, creator, Jack Maple]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jack Maple Context triple: [The District, creator, Jack Maple]
-
A.
Maples
Maples is the surname of Marla Maples, an American actress and television personality best known as the second wife of former U.S. President Donald Trump.
-
B.
Birch
Birch is a masculine given name most notably borne by American politician Birch Bayh, a long-serving U.S. senator from Indiana.
-
C.
Sugar maple
The sugar maple is a large, long-lived North American hardwood tree renowned for its brilliant fall foliage and as the primary source of maple syrup.
-
D.
Mountain Ash
Mountain Ash is a former coal-mining town and community in the Cynon Valley of Rhondda Cynon Taf, South Wales.
-
E.
Zelkova
Zelkova is a small genus of deciduous trees in the elm family, valued as ornamentals and for bonsai, and native to parts of Europe and Asia.
- 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: Jack Maple Triple: [The District, creator, Jack Maple]
Generated description
Jack Maple was an influential New York City transit police officer and crime strategist best known for co-developing the CompStat system that transformed modern policing.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jack Maple Target entity description: Jack Maple was an influential New York City transit police officer and crime strategist best known for co-developing the CompStat system that transformed modern policing.
-
A.
Maples
Maples is the surname of Marla Maples, an American actress and television personality best known as the second wife of former U.S. President Donald Trump.
-
B.
Birch
Birch is a masculine given name most notably borne by American politician Birch Bayh, a long-serving U.S. senator from Indiana.
-
C.
Sugar maple
The sugar maple is a large, long-lived North American hardwood tree renowned for its brilliant fall foliage and as the primary source of maple syrup.
-
D.
Mountain Ash
Mountain Ash is a former coal-mining town and community in the Cynon Valley of Rhondda Cynon Taf, South Wales.
-
E.
Zelkova
Zelkova is a small genus of deciduous trees in the elm family, valued as ornamentals and for bonsai, and native to parts of Europe and Asia.
- 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_69ad85a405e48190b6e68de7cf9f319e |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb1ee711481909c0d921f1b5b8562 |
completed | March 8, 2026, 5:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b31a946ba88190bd40ba7481baf28d |
completed | March 12, 2026, 7:57 p.m. |
| NEDg | Description generation | batch_69b31c3aaba48190b203e344d71080f3 |
completed | March 12, 2026, 8:04 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b31da28a04819096e7ced5f123592a |
completed | March 12, 2026, 8:10 p.m. |
Created at: March 8, 2026, 3:12 p.m.