Triple
T13065322
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomas |
E329306
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Tomas |
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: Tomas | Statement: [Thomas, hasVariant, Tomas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tomas Context triple: [Thomas, hasVariant, Tomas]
-
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.
Tomáš
Tomáš is a masculine given name commonly used in Czech and Slovak cultures, equivalent to Thomas in English.
-
C.
Tomasino
Tomasino is the colloquial term used to refer to students of the University of Santo Tomas in the Philippines.
-
D.
Tomasso
Tomasso is a character from the Marx Brothers’ classic comedy film "A Night at the Opera," contributing to the movie’s farcical and musical antics.
-
E.
Tobias
Tobias is the full given name of Toby Ziegler, the fictional White House Communications Director from the television series "The West Wing."
- 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_69d80771749c81909a6d9197b9504872 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d980eb81948190b27eb9ae19978079 |
completed | April 10, 2026, 10:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6d6016984819097c999772db1e831 |
completed | May 3, 2026, 4:58 a.m. |
Created at: April 9, 2026, 8:59 p.m.