Triple
T9117130
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cesar Romero |
E218748
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Cesar |
E190016
|
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: Cesar | Statement: [Cesar Romero, givenName, Cesar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cesar Context triple: [Cesar Romero, givenName, Cesar]
-
A.
Cesar
chosen
Cesar is a given name and surname used in various languages, commonly associated with the historical legacy of "Caesar" and borne by numerous notable figures in politics, arts, and sports.
-
B.
Ciro
Ciro is a masculine given name of Italian and Spanish origin, often used in various countries around the world.
-
C.
Lucio
Lucio is a Brazilian central defender renowned for his commanding presence, leadership, and success with both the Brazilian national team and top European clubs such as Bayern Munich and Inter Milan.
-
D.
Lucio
Lucio is a popular support hero in the game Overwatch, known for his music-based abilities that heal and speed up teammates.
-
E.
Lucio
Lucio is a roguish, witty gentleman in Shakespeare’s play "Measure for Measure," known for his bawdy humor, moral hypocrisy, and role as a comic commentator on the play’s themes of justice and corruption.
- 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_69ca83dc94ac8190b9ef42684d36ff39 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca8a4c9e08190ba3603a5d00afb20 |
completed | April 1, 2026, 5:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0307299ec8190acade4f388642e23 |
completed | April 3, 2026, 9:26 p.m. |
Created at: March 30, 2026, 7:17 p.m.