Triple
T6339432
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laura |
E142585
|
entity |
| Predicate | relatedName |
P3889
|
FINISHED |
| Object | Loren |
E532883
|
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: Loren | Statement: [Laura, relatedName, Loren]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Loren Context triple: [Laura, relatedName, Loren]
-
A.
Loren
chosen
Loren is a given name used for people of any gender, often as a variant or shortened form of names like Lorenzo or Lauren.
-
B.
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.
-
C.
Lesnie
Lesnie is the surname of Andrew Lesnie, the Academy Award–winning Australian cinematographer best known for his work on The Lord of the Rings film trilogy.
-
D.
Kaven
Kaven is one of the islands that make up Maloelap Atoll in the Marshall Islands, a Pacific island nation.
-
E.
Arvin
Arvin is a small agricultural city in Southern California’s San Joaquin Valley, known for its farming economy and diverse rural community.
- 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.