Triple
T1191513
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vincente Minnelli |
E25371
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Anthony |
E38636
|
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: Anthony | Statement: [Vincente Minnelli, givenName, Anthony]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anthony Context triple: [Vincente Minnelli, givenName, Anthony]
-
A.
Anthony
chosen
Anthony is a masculine given name of Latin origin, commonly used in English-speaking countries.
-
B.
Alan
Alan is a masculine given name of Celtic origin that has been widely used in English-speaking countries.
-
C.
Andrew
Andrew is a masculine given name of Greek origin meaning "manly" or "brave," widely used in English-speaking countries and beyond.
-
D.
Andrew
Andrew is a subway station in South Boston on the Massachusetts Bay Transportation Authority's Red Line.
-
E.
Ian
Ian is a masculine given name of Scottish Gaelic origin that has become widely used in English-speaking countries.
- 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_69a49427d98881908646d6c63b8cea1e |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd74e2c08190b4a48425f94addaa |
completed | March 1, 2026, 10:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acbf17a0cc819086da05f419e63e5a |
completed | March 8, 2026, 12:13 a.m. |
Created at: March 1, 2026, 7:45 p.m.