Triple
T12986605
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Teoh |
E321783
|
entity |
| Predicate | hasVariantSpelling |
P457
|
FINISHED |
| Object | Teo |
E321783
|
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: [Teoh, hasVariantSpelling, Teo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Teo Context triple: [Teoh, hasVariantSpelling, Teo]
-
A.
Teoh
chosen
Teoh is a romanized Chinese surname, commonly used as a variant spelling of "Zhang" in Southeast Asia.
-
B.
Teok
Teok is a town in the Jorhat district of Assam, India, known as a local commercial and transportation hub in the region.
-
C.
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.
-
D.
Theo
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.
-
E.
Tino
Tino is the commonly used nickname of former Major League Baseball first baseman Tino Martinez, best known for his years with the New York Yankees in the late 1990s and early 2000s.
- 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_69d8076479b8819090afce3591939cdf |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97e5f47ec8190b39107bc016f9824 |
completed | April 10, 2026, 10:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6b8f6245c8190867417c3ef1852e5 |
completed | May 3, 2026, 2:54 a.m. |
Created at: April 9, 2026, 8:40 p.m.