Triple
T16626031
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anastazy Walewski |
E403946
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Anastazy
Anastazy is a masculine given name of Polish origin, historically borne by several notable figures including nobles and clergy.
|
E1224737
|
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: Anastazy | Statement: [Anastazy Walewski, givenName, Anastazy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anastazy Context triple: [Anastazy Walewski, givenName, Anastazy]
-
A.
Anastas
Anastas is a masculine given name most notably borne by Soviet statesman Anastas Mikoyan.
-
B.
Anastasie
Anastasie is the given name of Anastasie de Lafayette, a French noblewoman associated with the influential Lafayette family.
-
C.
Antonina
Antonina was a prominent Byzantine noblewoman and influential wife of the famed general Belisarius, noted for her political acumen and close association with Empress Theodora in the 6th century.
-
D.
Antonina
Antonina is one of the three central women whose intertwined personal and professional lives are followed over several decades in the Soviet drama film "Moscow Does Not Believe in Tears."
-
E.
Antonina
Antonina is a historical novel by Wilkie Collins set in ancient Rome during the Gothic siege of the city.
- 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: Anastazy Triple: [Anastazy Walewski, givenName, Anastazy]
Generated description
Anastazy is a masculine given name of Polish origin, historically borne by several notable figures including nobles and clergy.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Anastazy Target entity description: Anastazy is a masculine given name of Polish origin, historically borne by several notable figures including nobles and clergy.
-
A.
Anastas
Anastas is a masculine given name most notably borne by Soviet statesman Anastas Mikoyan.
-
B.
Anastasie
Anastasie is the given name of Anastasie de Lafayette, a French noblewoman associated with the influential Lafayette family.
-
C.
Antonina
Antonina was a prominent Byzantine noblewoman and influential wife of the famed general Belisarius, noted for her political acumen and close association with Empress Theodora in the 6th century.
-
D.
Antonina
Antonina is one of the three central women whose intertwined personal and professional lives are followed over several decades in the Soviet drama film "Moscow Does Not Believe in Tears."
-
E.
Antonina
Antonina is a historical novel by Wilkie Collins set in ancient Rome during the Gothic siege of the city.
- 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_69d883897eb481909eaaa088ba9918d9 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e375530ed081908337dc5c6360d733 |
completed | April 18, 2026, 12:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a007dba91bc819090a78ac4c0c01fc8 |
completed | May 10, 2026, 12:44 p.m. |
| NEDg | Description generation | batch_6a007e747eac81908b0b5a2072a177dd |
completed | May 10, 2026, 12:47 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a007f75e7e48190ac5cf912cca60d9c |
completed | May 10, 2026, 12:52 p.m. |
Created at: April 10, 2026, 5:17 a.m.