Triple
T10935506
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monarch |
E258321
|
entity |
| Predicate | notableMember |
P10
|
FINISHED |
| Object | Nathan Lind |
E792810
|
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: Nathan Lind | Statement: [Monarch, notableMember, Nathan Lind]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nathan Lind Context triple: [Monarch, notableMember, Nathan Lind]
-
A.
Nathan Lind
chosen
Nathan Lind is a geologist and former Monarch scientist in the MonsterVerse franchise who helps orchestrate the expedition into the Hollow Earth in "Godzilla vs. Kong."
-
B.
Nathan Larson
Nathan Larson is an American musician and film composer known for scoring numerous independent and mainstream movies.
-
C.
Nathan Johnson
Nathan Johnson is an American film composer and musician best known for his innovative, experimental scores for director Rian Johnson’s movies, including "Brick," "Looper," and "Knives Out."
-
D.
Nathan Young
Nathan Young is a musician best known as a member of the American alternative rock band Anberlin, where he serves as the drummer.
-
E.
Trent Baalke
Trent Baalke is an American football executive best known for his tenure as an NFL general manager, including leading front offices for multiple franchises.
- 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_69d6aa8769b4819082bfe5e61b9017f0 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d770aee178819082c1671a37ff7d82 |
completed | April 9, 2026, 9:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e23bee9b208190aee8f938dff3f234 |
completed | April 17, 2026, 1:55 p.m. |
Created at: April 8, 2026, 9:23 p.m.