Triple
T20663757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ed McBain |
E507826
|
entity |
| Predicate | notableCharacter |
P1481
|
FINISHED |
| Object |
Meyer Meyer
Meyer Meyer is a fictional detective and key member of the 87th Precinct in Ed McBain’s long-running police procedural novel series.
|
E1444528
|
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: Meyer Meyer | Statement: [Ed McBain, notableCharacter, Meyer Meyer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Meyer Meyer Context triple: [Ed McBain, notableCharacter, Meyer Meyer]
-
A.
Meyer
Meyer is a common German-origin surname borne by numerous notable individuals across fields such as literature, entertainment, sports, and academia.
-
B.
Meyer
Meyer is a given name most famously associated with Meyer Lansky, a major organized crime figure in the United States during the 20th century.
-
C.
Meier
Meier is a common German surname borne by numerous individuals across various professions and regions.
-
D.
Meyer-Hetling
Meyer-Hetling is a German surname most notably associated with Konrad Meyer-Hetling, an agronomist and SS officer involved in Nazi settlement planning.
-
E.
Meyerhof
Meyerhof is a surname of German origin, notably borne by biochemist Otto Fritz Meyerhof, a Nobel laureate recognized for his work on muscle metabolism.
- 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: Meyer Meyer Triple: [Ed McBain, notableCharacter, Meyer Meyer]
Generated description
Meyer Meyer is a fictional detective and key member of the 87th Precinct in Ed McBain’s long-running police procedural novel series.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Meyer Meyer Target entity description: Meyer Meyer is a fictional detective and key member of the 87th Precinct in Ed McBain’s long-running police procedural novel series.
-
A.
Meyer
Meyer is a common German-origin surname borne by numerous notable individuals across fields such as literature, entertainment, sports, and academia.
-
B.
Meyer
Meyer is a given name most famously associated with Meyer Lansky, a major organized crime figure in the United States during the 20th century.
-
C.
Meier
Meier is a common German surname borne by numerous individuals across various professions and regions.
-
D.
Meyer-Hetling
Meyer-Hetling is a German surname most notably associated with Konrad Meyer-Hetling, an agronomist and SS officer involved in Nazi settlement planning.
-
E.
Meyerhof
Meyerhof is a surname of German origin, notably borne by biochemist Otto Fritz Meyerhof, a Nobel laureate recognized for his work on muscle metabolism.
- 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_69e0b4c059bc81908ea762cd73ea4424 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6b2f541bc8190ac7946b91647f2b0 |
completed | April 20, 2026, 11:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a08cd5d0da481909eebd69b8b314503 |
completed | May 16, 2026, 8:02 p.m. |
| NEDg | Description generation | batch_6a08d175206c8190b119bb1a2d06462f |
completed | May 16, 2026, 8:20 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a08d293523c8190aaa01c6c73c9afd5 |
completed | May 16, 2026, 8:24 p.m. |
Created at: April 16, 2026, 11:44 a.m.