Triple
T985406
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Benjamin Siegel |
E21266
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Siegel |
E21266
|
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: Siegel | Statement: [Benjamin Siegel, familyName, Siegel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Siegel Context triple: [Benjamin Siegel, familyName, Siegel]
-
A.
Siegel
chosen
Siegel is the surname of Benjamin "Bugsy" Siegel, the infamous American mobster who played a key role in the development of Las Vegas.
-
B.
Blaustein
Blaustein is a municipality in the Alb-Donau district of Baden-Württemberg in southern Germany, situated near the city of Ulm.
-
C.
Sigd
Sigd is a Jewish holiday of Ethiopian origin that combines fasting, prayer, and communal celebration to reaffirm the covenant with God and the longing for Jerusalem.
-
D.
Sieg
The Sieg is a river in western Germany that flows through North Rhine-Westphalia and Rhineland-Palatinate before joining the Rhine.
-
E.
Ehrlich
Ehrlich is a German-origin surname borne by numerous notable individuals across fields such as science, medicine, and the arts.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69a493c383dc8190a03257f22d4b4183 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b4959fe48190a78bd811cbc888ab |
completed | March 1, 2026, 9:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac1ce3c6fc81909fbbf04eef1b997e |
completed | March 7, 2026, 12:41 p.m. |
Created at: March 1, 2026, 7:41 p.m.