Triple
T1146349
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Morten Lie |
E23574
|
entity |
| Predicate | hasFamilyName |
P18
|
FINISHED |
| Object | Lie |
E107482
|
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: Lie | Statement: [Morten Lie, hasFamilyName, Lie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lie Context triple: [Morten Lie, hasFamilyName, Lie]
-
A.
LIE
chosen
LIE is the three-letter ISO 3166-1 alpha-3 country code assigned to the Principality of Liechtenstein.
-
B.
One of My Lies
"One of My Lies" is a song by the American punk rock band Green Day from their early studio album "Kerplunk."
-
C.
Vérité
Vérité is a socially engaged novel by Émile Zola that denounces anti-Semitism and religious intolerance in France, inspired by the Dreyfus Affair.
-
D.
Liar Liar
Liar Liar is a 1997 comedy film starring Jim Carrey as a fast-talking lawyer magically compelled to tell the truth for 24 hours, leading to a series of chaotic and humorous consequences.
-
E.
A Liar’s Autobiography
A Liar’s Autobiography is a surreal, comedic memoir by Monty Python member Graham Chapman that blends fact and fiction to chronicle his life and career.
- 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_69a493ef399c8190b04b9146d2314f59 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4bc6e8c2081909fb3534413b7aacb |
completed | March 1, 2026, 10:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac5eb1f7d08190ba722dcbbc8a6799 |
completed | March 7, 2026, 5:21 p.m. |
Created at: March 1, 2026, 7:44 p.m.