Triple
T3935552
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alexis |
E90901
|
entity |
| Predicate | hasCognate |
P2525
|
FINISHED |
| Object | Alejandro |
E39964
|
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: Alejandro | Statement: [Alexis, hasCognate, Alejandro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alejandro Context triple: [Alexis, hasCognate, Alejandro]
-
A.
Alejandro
chosen
Alejandro is the Spanish form of the given name Alexander, commonly used in Spanish-speaking countries.
-
B.
Guillermo
Guillermo is the Spanish form of the given name William, commonly used in Spanish-speaking countries.
-
C.
Vicente
Vicente is a given name, common in Spanish- and Portuguese-speaking countries, that corresponds to the English name Vincent.
-
D.
Julio
Julio is the given name of Julio Antonio Mella, a prominent early 20th-century Cuban communist leader and co-founder of the Cuban Communist Party.
-
E.
Enrique
Enrique is a Spanish given name equivalent to the English name Henry.
- 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_69aed95f26e0819094b0e71974543a19 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeedcd29148190a98e4549c9ed8888 |
completed | March 9, 2026, 3:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5288eb3e481909a68531fd37371a4 |
completed | March 14, 2026, 9:21 a.m. |
Created at: March 9, 2026, 3:23 p.m.