Triple
T8950649
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sam Mills |
E213336
|
entity |
| Predicate | hasChild |
P369
|
FINISHED |
| Object | Sam Mills III |
E213336
|
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: Sam Mills III | Statement: [Sam Mills, hasChild, Sam Mills III]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sam Mills III Context triple: [Sam Mills, hasChild, Sam Mills III]
-
A.
Sam Mills
chosen
Sam Mills was a standout undersized linebacker and team leader in the NFL, best known for his Pro Bowl play and inspirational presence with the New Orleans Saints and Carolina Panthers.
-
B.
Dane Mills
Dane Mills is a musician best known as an early member of the Canadian indie rock band Arcade Fire.
-
C.
Miles Smith
Miles Smith was an English theologian and bishop best known as one of the principal translators and editors of the King James Version of the Bible.
-
D.
Miles Drentell
Miles Drentell is a manipulative, morally ambiguous advertising executive and recurring antagonist on the television drama "thirtysomething."
-
E.
Miles Malleson
Miles Malleson was an English actor, playwright, and screenwriter known for his character roles in British cinema and his adaptations of classic works for stage and film.
- 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_69ca839843408190a39069a029a89f15 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc670c7244819084978922a9835bc9 |
completed | April 1, 2026, 12:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfc20a5ab481909e10f3abf679ec4c |
completed | April 3, 2026, 1:35 p.m. |
Created at: March 30, 2026, 6:59 p.m.