Triple
T21335675
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sam Giancana |
E526038
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object |
Momo
Momo is the underworld nickname of Sam Giancana, a powerful mid-20th-century Chicago mob boss and key figure in the American Mafia.
|
E1478896
|
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: Momo | Statement: [Sam Giancana, nickname, Momo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Momo Context triple: [Sam Giancana, nickname, Momo]
-
A.
Momo
Momo is the young, troubled Jewish boy who forms a transformative friendship with the elderly Muslim shopkeeper in Éric-Emmanuel Schmitt’s novella *Monsieur Ibrahim and the Flowers of the Koran*.
-
B.
Momo
Momo is a Japanese singer, rapper, and main dancer best known as a member of the South Korean girl group Twice.
-
C.
Les Muma
Les Muma is an American businessman and philanthropist best known for his major contributions to the University of South Florida, where the business school bears his name.
-
D.
Ein Kind
Ein Kind is an autobiographical work by Austrian writer Thomas Bernhard that recounts his bleak and formative childhood experiences.
-
E.
Die Kinder
Die Kinder is a 1990 British television drama miniseries about political intrigue and personal danger surrounding a couple searching for their missing children in Europe.
- 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: Momo Triple: [Sam Giancana, nickname, Momo]
Generated description
Momo is the underworld nickname of Sam Giancana, a powerful mid-20th-century Chicago mob boss and key figure in the American Mafia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Momo Target entity description: Momo is the underworld nickname of Sam Giancana, a powerful mid-20th-century Chicago mob boss and key figure in the American Mafia.
-
A.
Momo
Momo is the young, troubled Jewish boy who forms a transformative friendship with the elderly Muslim shopkeeper in Éric-Emmanuel Schmitt’s novella *Monsieur Ibrahim and the Flowers of the Koran*.
-
B.
Momo
Momo is a Japanese singer, rapper, and main dancer best known as a member of the South Korean girl group Twice.
-
C.
Les Muma
Les Muma is an American businessman and philanthropist best known for his major contributions to the University of South Florida, where the business school bears his name.
-
D.
Ein Kind
Ein Kind is an autobiographical work by Austrian writer Thomas Bernhard that recounts his bleak and formative childhood experiences.
-
E.
Die Kinder
Die Kinder is a 1990 British television drama miniseries about political intrigue and personal danger surrounding a couple searching for their missing children in Europe.
- 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_69e0b51c33048190ab27cede74ef798c |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e898d6fcbc8190b83d9cfc9b4ca123 |
completed | April 22, 2026, 9:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a09a5c260dc8190be7acb83b1c9c832 |
completed | May 17, 2026, 11:25 a.m. |
| NEDg | Description generation | batch_6a09a8aef61c8190985aad0637b8fadd |
completed | May 17, 2026, 11:38 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a09a915a57c81909b5b1bb7042957a0 |
completed | May 17, 2026, 11:40 a.m. |
Created at: April 16, 2026, 4:43 p.m.