Triple
T8003573
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lorin Maazel |
E186310
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Lorin |
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: Lorin | Statement: [Lorin Maazel, givenName, Lorin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lorin Context triple: [Lorin Maazel, givenName, Lorin]
-
A.
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.
-
B.
Arliss
"Arliss" is an American comedy television series that satirically follows a ruthless sports agent navigating the business and ethical dilemmas of professional athletics.
-
C.
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.
-
D.
Larue
Larue is a Vietnamese beer brand produced by Asia Pacific Breweries, known for its pale lager popular in central Vietnam.
-
E.
Rilland
Rilland is a village in the Dutch province of Zeeland, located on the island of Zuid-Beveland.
- 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_69ca82aaaf24819084b94d18f699ba53 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3cf443e48190ac9e83343ff4019e |
completed | March 31, 2026, 3:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc5697ac9081909fe7ca06d0c3ef38 |
completed | March 31, 2026, 11:19 p.m. |
Created at: March 30, 2026, 5:18 p.m.