Triple
T1128424
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Antonin Scalia |
E24773
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Antonin
Antonin is a masculine given name most notably borne by Antonin Scalia, a former Associate Justice of the United States Supreme Court.
|
E129866
|
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: Antonin | Statement: [Antonin Scalia, givenName, Antonin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Antonin Context triple: [Antonin Scalia, givenName, Antonin]
-
A.
Antoine
Antoine is the given name of Antoine de la Mothe Cadillac, the French explorer and founder of Detroit.
-
B.
René
René is a French given name commonly used for males and historically associated with several notable figures in politics, arts, and philosophy.
-
C.
Théodore
Théodore is a masculine given name of Greek origin, commonly used in French-speaking countries and borne by notable figures such as the Reformation theologian Théodore Beza.
-
D.
Klemens
Klemens is a given name, primarily used in German-speaking and Central European countries, that corresponds to the Latin-derived name Clemens.
-
E.
Pierre
Pierre is a masculine given name of French origin that has been borne by numerous notable figures in history, arts, and science.
- 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: Antonin Triple: [Antonin Scalia, givenName, Antonin]
Generated description
Antonin is a masculine given name most notably borne by Antonin Scalia, a former Associate Justice of the United States Supreme Court.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Antonin Target entity description: Antonin is a masculine given name most notably borne by Antonin Scalia, a former Associate Justice of the United States Supreme Court.
-
A.
Antoine
Antoine is the given name of Antoine de la Mothe Cadillac, the French explorer and founder of Detroit.
-
B.
René
René is a French given name commonly used for males and historically associated with several notable figures in politics, arts, and philosophy.
-
C.
Théodore
Théodore is a masculine given name of Greek origin, commonly used in French-speaking countries and borne by notable figures such as the Reformation theologian Théodore Beza.
-
D.
Klemens
Klemens is a given name, primarily used in German-speaking and Central European countries, that corresponds to the Latin-derived name Clemens.
-
E.
Pierre
Pierre is a masculine given name of French origin that has been borne by numerous notable figures in history, arts, and science.
- 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_69a4940712c88190aa244f3fc6070a65 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bbdea9b88190a88da718bf5c1897 |
completed | March 1, 2026, 10:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac59a82bb8819084f77aff9af653c0 |
completed | March 7, 2026, 5 p.m. |
| NEDg | Description generation | batch_69ac5a97f1408190855d8ea4f4317b07 |
completed | March 7, 2026, 5:04 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac5b1b5930819098f511db269e991d |
completed | March 7, 2026, 5:06 p.m. |
Created at: March 1, 2026, 7:44 p.m.