Triple
T3001182
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zhang |
E81790
|
entity |
| Predicate | hasVariantTransliteration |
P5923
|
FINISHED |
| Object | Teo |
E41209
|
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: Teo | Statement: [Zhang, hasVariantTransliteration, Teo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Teo Context triple: [Zhang, hasVariantTransliteration, Teo]
-
A.
Tejo
Tejo is the Portuguese name for the Tagus River, the longest river on the Iberian Peninsula that flows through Spain and Portugal into the Atlantic Ocean.
-
B.
Theo
chosen
Theo is a given name, often used as a short form of Theodore or related names, that has become a popular standalone first name in many countries.
-
C.
Thea
Thea is a feminine given name, often used as a short form of names like Dorothea or Theodora and associated with the Greek word for "goddess."
-
D.
Joyo
Joyo is a small city in Japan known for its location in Kyoto Prefecture and its blend of residential areas, light industry, and historical sites.
-
E.
Théo
Théo is a French given name, typically a short form of Théodore, commonly used for boys in French-speaking countries.
- 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_69ad8b1c4de88190a83b7cefaa1f2842 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9a1022e48190afee77db94635ff2 |
completed | March 8, 2026, 3:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b12e4b54188190bf900bf10061a57a |
completed | March 11, 2026, 8:56 a.m. |
Created at: March 8, 2026, 2:59 p.m.