Triple
T3372606
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matthew |
E70988
|
entity |
| Predicate | hasCognate |
P2525
|
FINISHED |
| Object | Mateo |
E153306
|
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: Mateo | Statement: [Matthew, hasCognate, Mateo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mateo Context triple: [Matthew, hasCognate, Mateo]
-
A.
Mateo
chosen
Mateo is a masculine given name of Spanish origin, commonly used in Spanish-speaking countries and derived from the Hebrew name Matthew, meaning "gift of God."
-
B.
Mateus
Mateus is a Portuguese surname commonly borne by individuals such as Rui Mateus.
-
C.
Matteo
Matteo is the Italian given name equivalent to Matthew, commonly used in Italy and other Italian-speaking communities.
-
D.
Lukas
Lukas is a masculine given name commonly used in various European countries, often associated with the biblical name Luke.
-
E.
Luis
Luis is a comedic supporting character in the Marvel Cinematic Universe, best known as Scott Lang’s fast-talking friend and former cellmate in the Ant-Man films.
- 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_69ad85a729d48190afd789cd8417f289 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb2bdcf70819087fc7e00fbd61e0d |
completed | March 8, 2026, 5:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b34bbfaf3081908babba216c7da776 |
completed | March 12, 2026, 11:26 p.m. |
Created at: March 8, 2026, 3:13 p.m.