Triple
T6376568
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tomas |
E143480
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Tomàs |
E143480
|
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: Tomàs | Statement: [Tomas, hasVariant, Tomàs]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tomàs Context triple: [Tomas, hasVariant, Tomàs]
-
A.
Tomas
chosen
Tomas is a masculine given name commonly used in various European and Latin American countries, often equivalent to "Thomas" in English.
-
B.
Tomasino
Tomasino is the colloquial term used to refer to students of the University of Santo Tomas in the Philippines.
-
C.
Tomáš
Tomáš is a masculine given name commonly used in Czech and Slovak cultures, equivalent to Thomas in English.
-
D.
Tommaso
Tommaso is the given name of Thomas Francis, Prince of Carignano, a 17th-century Italian nobleman of the House of Savoy.
-
E.
Timoteo
Timoteo is a masculine given name, commonly used in Romance-language countries, derived from the biblical name Timothy.
- 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_69c008d9f4348190ab598a2913259a1c |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0683bfc7081908b15c3c9a3c72e7b |
completed | March 22, 2026, 10:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c638724d448190a7f13a7c449341db |
completed | March 27, 2026, 7:57 a.m. |
Created at: March 22, 2026, 4:33 p.m.