Triple
T12559542
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lowe |
E295304
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Lowe |
E295304
|
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: Lowe | Statement: [Lowe, hasVariant, Lowe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lowe Context triple: [Lowe, hasVariant, Lowe]
-
A.
Lowe
chosen
Lowe is a common English surname of Anglo-Saxon origin, often derived from the Old English word for a small hill or burial mound.
-
B.
Lowe-Porter
Lowe-Porter is a surname most notably associated with H. T. Lowe-Porter, the English translator renowned for bringing Thomas Mann’s works into English.
-
C.
Talbot
Talbot is a surname of English and Norman origin, historically associated with several notable families and individuals.
-
D.
Barlow
Barlow is a surname most notably associated with John Perry Barlow, the American poet, essayist, and co-founder of the Electronic Frontier Foundation.
-
E.
Winstone
Winstone is an English surname most notably borne by actor Ray Winstone, known for his tough-guy roles in film and television.
- 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_69d6ad9cac2c81908e8a7bed82d1e21d |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d95491d9688190a6b88a939124233e |
completed | April 10, 2026, 7:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6558b307c81909ec5407af013de1d |
completed | May 2, 2026, 7:50 p.m. |
Created at: April 8, 2026, 11:48 p.m.