Triple
T6339422
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laura |
E142585
|
entity |
| Predicate | hasDiminutive |
P456
|
FINISHED |
| Object | Lauri |
E203471
|
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: Lauri | Statement: [Laura, hasDiminutive, Lauri]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lauri Context triple: [Laura, hasDiminutive, Lauri]
-
A.
Lauri
chosen
Lauri is a Finnish given name commonly used for men, notably borne by former President of Finland Lauri Kristian Relander.
-
B.
Laur
Laur is a rural municipality in the province of Nueva Ecija in the Philippines, known for its agricultural landscape and proximity to the Sierra Madre mountain range.
-
C.
Lari
Lari is a regional dialect of the Sindhi language spoken primarily in parts of Sindh, Pakistan.
-
D.
Luri
Luri is a Southwestern Iranian language spoken primarily by the Lur people in western and southwestern Iran.
-
E.
Lorens
Lorens is a character from Paulo Coelho’s novel "Brida," serving as one of the key figures in the protagonist’s spiritual and personal journey.
- 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_69c008d5ab108190b346c465696824a9 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0654fb774819087bffb8b966a790a |
completed | March 22, 2026, 9:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c604352f148190b5accc28462256ad |
completed | March 27, 2026, 4:14 a.m. |
Created at: March 22, 2026, 4:30 p.m.