Triple
T15806990
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stephenie Meyer |
E383242
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Christian Meyer |
E383242
|
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: Christian Meyer | Statement: [Stephenie Meyer, spouse, Christian Meyer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Christian Meyer Context triple: [Stephenie Meyer, spouse, Christian Meyer]
-
A.
Christian Meyer
chosen
Christian Meyer is the husband of American author Stephenie Meyer, best known for her Twilight series.
-
B.
Christian Roth
Christian Roth was a mountaineer known for participating in the first recorded ascent of Shkhara, one of the highest peaks in the Caucasus.
-
C.
Christian Weiss
Christian Weiss is a relatively obscure individual whose specific public notability is not clearly established from the given information.
-
D.
Matthias Koenigswieser
Matthias Koenigswieser is a cinematographer known for his work on feature films such as the live-action Disney movie "Christopher Robin."
-
E.
Eric Meyhofer
Eric Meyhofer is a technology executive best known for leading Uber’s self-driving car efforts as head of the Uber Advanced Technologies Group.
- 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_69d86da2858c819090cc8481e7207b6e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b52751348190964e82463ce9dd20 |
completed | April 16, 2026, 10:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffeb7f3c9481908bdde67998263c5e |
completed | May 10, 2026, 2:20 a.m. |
Created at: April 10, 2026, 4:48 a.m.