Triple
T23207440
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liv Lerner |
E580497
|
entity |
| Predicate | hasFiancé |
P17846
|
FINISHED |
| Object | Daniel |
—
|
NE NERFINISHED |
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: Daniel | Statement: [Liv Lerner, hasFiancé, Daniel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daniel Context triple: [Liv Lerner, hasFiancé, Daniel]
-
A.
Daniel
Daniel is a biblical book in the Old Testament that recounts the visions and experiences of the prophet Daniel, emphasizing themes of faithfulness and divine sovereignty.
-
B.
Daniel
chosen
Daniel is a masculine given name of Hebrew origin commonly used in many cultures and languages.
-
C.
Daniel
Daniel is a prominent mountain peak in the Northern Limestone Alps of Germany, known for being the highest summit in the Ammergau Alps.
-
D.
Jeru the Damaja
Jeru the Damaja is a Brooklyn-born American rapper known for his socially conscious lyrics, complex wordplay, and influential work in 1990s East Coast hip hop.
-
E.
Adam
Adam is a person who enjoys or benefits from eating lasagne.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e24602ae1481908aaa6bc7ca493867 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1907d8be08190a100d99efaff9964 |
completed | April 29, 2026, 5 a.m. |
Created at: April 17, 2026, 4:07 p.m.