Triple
T15140878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hugh Low |
E361678
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Hugh Low |
E361678
|
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: Hugh Low | Statement: [Hugh Low, name, Hugh Low]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hugh Low Context triple: [Hugh Low, name, Hugh Low]
-
A.
Hugh Low
chosen
Hugh Low was a 19th-century British colonial administrator and naturalist best known for leading the first recorded ascent of Mount Kinabalu in Borneo.
-
B.
Cecil Brown
Cecil Brown is a name shared by several notable individuals, including an American novelist and academic, a World War II war correspondent, and a British politician.
-
C.
Russell Hill
Russell Hill is a locality in Canberra, Australia, situated close to the parliamentary precinct of Capital Hill.
-
D.
Nigel Lane
Nigel Lane is a relatively obscure individual whose primary public mention appears to be as a namesake in reference data, with no widely documented achievements or roles.
-
E.
Richard Grove
Richard Grove is an American actor best known for his supporting role in the cult horror-comedy film "Army of Darkness."
- 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_69d85a0759908190b8a051d2e2a1cbe6 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e005c46a248190a2364092d40274f3 |
completed | April 15, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69febfec3ae48190b2d8e853dab00777 |
completed | May 9, 2026, 5:02 a.m. |
Created at: April 10, 2026, 3:07 a.m.