Triple
T1454282
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lê |
E31362
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Ly |
E31362
|
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: Ly | Statement: [Lê, hasVariant, Ly]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ly Context triple: [Lê, hasVariant, Ly]
-
A.
Lu
Lu is the traditional abbreviation and historical name used to refer to China’s Shandong province.
-
B.
Le
chosen
Le is a common Vietnamese surname shared by many notable figures in the country’s history and culture.
-
C.
LI
LI is the Roman numeral representing the number 51.
-
D.
L
L is the enigmatic, emotionally complex protagonist of Hanne Ørstavik’s novel "Love," whose inner life and perspective drive the story’s exploration of isolation and longing.
-
E.
L
The L is a Chicago 'L' rapid transit line that serves the city’s West Side and western suburbs as part of the Chicago Transit Authority system.
- 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_69a499171a28819085b993a3ac78e363 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c57fead881909a47188ce7312406 |
completed | March 1, 2026, 11:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad0e71ffd481909dfd0f77201dc17c |
completed | March 8, 2026, 5:51 a.m. |
Created at: March 1, 2026, 8 p.m.