Triple
T9131970
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ruben Santiago-Hudson |
E219107
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Ruben |
E187239
|
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: Ruben | Statement: [Ruben Santiago-Hudson, givenName, Ruben]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ruben Context triple: [Ruben Santiago-Hudson, givenName, Ruben]
-
A.
Rubén
chosen
Rubén is a masculine given name of Spanish origin commonly used in Spanish-speaking countries.
-
B.
Roberto
Roberto is a masculine given name commonly used in Romance-language countries, equivalent to the English name Robert.
-
C.
Jorge
Jorge is a masculine given name of Spanish and Portuguese origin, equivalent to George in English.
-
D.
Jorge
Jorge is a character portrayed by actor Giancarlo Esposito, known for his nuanced and often intense roles in film and television.
-
E.
Jorge
Jorge is the central character of Robert Silverberg’s science fiction novella "Born with the Dead," set in a future where the dead can be partially revived and live apart from the living.
- 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_69ca83debfc0819095800583e97ab10f |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca8db7d808190bd22b0e5a6f9c285 |
completed | April 1, 2026, 5:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d047dc25208190a720910e6d43199b |
completed | April 3, 2026, 11:06 p.m. |
Created at: March 30, 2026, 7:18 p.m.