Triple
T5932949
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Edu Weitzel Douwes Dekker |
E131978
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Edu |
E234465
|
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: Edu | Statement: [Edu Weitzel Douwes Dekker, givenName, Edu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Edu Context triple: [Edu Weitzel Douwes Dekker, givenName, Edu]
-
A.
Edu
Edu is a local government area in Kwara State, Nigeria, known for its predominantly Nupe-speaking communities and agrarian economy.
-
B.
Edu
chosen
Edu is a common shortened form of the given name Eduardo, often used as an informal nickname.
-
C.
education commands
Education commands are specialized military organizations responsible for overseeing and delivering training and professional development to service members within a larger training and education structure.
-
D.
Ed
Ed is a common masculine given name, typically used as a short form of names such as Edward, Edwin, or Edmund.
-
E.
ED
ED is the federal agency responsible for establishing policy, administering, and coordinating most education-related programs in the United States.
- 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_69c0085c55dc8190aa90e242c956e2fa |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0389df18c81909027a9db7596f0c1 |
completed | March 22, 2026, 6:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0c064d2a4819096085668182cfde1 |
completed | March 23, 2026, 4:24 a.m. |
Created at: March 22, 2026, 4 p.m.