Triple
T8234613
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mateo Messi |
E192373
|
entity |
| Predicate | givenName |
P17
|
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: [Mateo Messi, givenName, Mateo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mateo Context triple: [Mateo Messi, givenName, 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.
Matias
Matias is a masculine given name of Hebrew origin, related to names like Mateo and Matthew, commonly used in Spanish- and Portuguese-speaking countries.
-
D.
Matteo
Matteo is the Italian given name equivalent to Matthew, commonly used in Italy and other Italian-speaking communities.
-
E.
Lukas
Lukas is a masculine given name commonly used in various European countries, often associated with the biblical name Luke.
- 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_69ca82dc8f148190a2c75a98501a7b91 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb782931848190bcc54622f34e06a7 |
completed | March 31, 2026, 7:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd34f0a770819089520e689ca9937a |
completed | April 1, 2026, 3:08 p.m. |
Created at: March 30, 2026, 5:46 p.m.