Triple
T5108187
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manuel Tagüeña |
E115149
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Manuel |
E450874
|
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: Manuel | Statement: [Manuel Tagüeña, givenName, Manuel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Manuel Context triple: [Manuel Tagüeña, givenName, Manuel]
-
A.
Manuel
Manuel is the given name of Manny Ramirez, the former Major League Baseball star known for his powerful hitting and tenure with the Boston Red Sox.
-
B.
Manuel
Manuel is the hapless, linguistically challenged Spanish waiter from the British sitcom "Fawlty Towers," known for his comedic misunderstandings and clashes with Basil Fawlty.
-
C.
Manuel
Manuel was the given name of Manuel II, the last King of Portugal who reigned in the early 20th century.
-
D.
Manuel
chosen
Manuel is a masculine given name of Hebrew origin, commonly used in Spanish- and Portuguese-speaking countries and derived from "Emmanuel," meaning "God is with us."
-
E.
Francisco
Francisco is a masculine given name of Spanish and Portuguese origin, equivalent to Francis in English.
- 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_69bd4440b3348190be1251fd8b7951f1 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd75aa6b088190b02cdb66ec4a11f0 |
completed | March 20, 2026, 4:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69beba9ec0fc819085dcd1d27f46f377 |
completed | March 21, 2026, 3:34 p.m. |
Created at: March 20, 2026, 1:41 p.m.