Triple
T2383003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trevor |
E46353
|
entity |
| Predicate | hasVariantSpelling |
P457
|
FINISHED |
| Object | Trever |
E46353
|
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: Trever | Statement: [Trevor, hasVariantSpelling, Trever]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Trever Context triple: [Trevor, hasVariantSpelling, Trever]
-
A.
Treveris
Treveris is the historical city now known as Trier, one of the oldest cities in Germany and a major center of the Roman Empire in the region.
-
B.
Trevor
chosen
Trevor is a masculine given name of English origin commonly used in the UK and other English-speaking countries.
-
C.
Trevor Jim
Trevor Jim was a computer scientist and cryptographer known for his work on programming languages, security, and formal methods.
-
D.
Tabio
Tabio is a small Colombian town in the department of Cundinamarca, known for its cool climate, agricultural traditions, and proximity to Bogotá.
-
E.
Zeke
Zeke is a central male character in the romantic comedy film "Think Like a Man," known for navigating modern dating dynamics alongside a group of friends influenced by a relationship advice book.
- 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_69a88a1554a48190a0180682bcf099be |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abc7bafa248190a68e8f1e081f4817 |
completed | March 7, 2026, 6:37 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aea8b790bc8190ba399e252acec750 |
completed | March 9, 2026, 11:02 a.m. |
Created at: March 4, 2026, 7:57 p.m.