Triple
T8737973
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Walter Matthau |
E207432
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Matthau |
E744150
|
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: Matthau | Statement: [Walter Matthau, familyName, Matthau]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matthau Context triple: [Walter Matthau, familyName, Matthau]
-
A.
Matthau
chosen
Matthau is a surname most famously associated with American actor Walter Matthau and his family, including his son, director Charles Matthau.
-
B.
Menzel Horr
Menzel Horr is a town in northeastern Tunisia known for its agricultural surroundings and its location within the coastal Nabeul region.
-
C.
Matta
Matta is a surname most prominently associated with Thad Matta, a successful American college basketball coach known for his tenures at Xavier and Ohio State.
-
D.
Matta
Matta is a town located in Pakistan’s Swat District, known for its agricultural surroundings and scenic mountainous landscape.
-
E.
Матуа
Матуа — это вулканический остров в центральной части Курильской гряды, известный своим действующим вулканом Сарычева и стратегическим военным значением.
- 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_69ca835a03a081909d4d4cd01a18c9fb |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5d470c8c81909ead395ef704c6ba |
completed | March 31, 2026, 11:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf42c9140081909f9c10560757c860 |
completed | April 3, 2026, 4:32 a.m. |
Created at: March 30, 2026, 6:38 p.m.