Triple
T20995480
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Donald Woods |
E517136
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Hobeni |
—
|
NE NERFINISHED |
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: Hobeni | Statement: [Donald Woods, placeOfBirth, Hobeni]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hobeni Context triple: [Donald Woods, placeOfBirth, Hobeni]
-
A.
Hozat
Hozat is a small town and district in eastern Turkey known for its mountainous terrain and predominantly Alevi Kurdish population.
-
B.
Bergville
chosen
Bergville is a small town in KwaZulu-Natal, South Africa, serving as a gateway to the northern Drakensberg mountain region.
-
C.
Città Beland
Città Beland is a historical title referring to the Maltese town of Żejtun, known for its rich cultural heritage and traditional architecture.
-
D.
Tivissa
Tivissa is a historic village in Catalonia, Spain, known for its scenic setting among the mountains of the Ribera d’Ebre region and its well-preserved medieval core.
-
E.
Tushingham
Tushingham is an English surname most notably associated with Rita Tushingham, a celebrated British actress known for her roles in 1960s cinema.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b5006e2881909fc2383f841740cc |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fc1fd5d48190a56981cee95ebd69 |
completed | April 21, 2026, 4:25 a.m. |
Created at: April 16, 2026, 1:50 p.m.