Triple
T23477341
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | How I Met Your Father |
E570298
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Chris Lowell |
—
|
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: Chris Lowell | Statement: [How I Met Your Father, starring, Chris Lowell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chris Lowell Context triple: [How I Met Your Father, starring, Chris Lowell]
-
A.
Chris Lowell
chosen
Chris Lowell is an American actor best known for his roles in television series such as "Veronica Mars," "Private Practice," and "GLOW," as well as films like "Up in the Air."
-
B.
Patrick Whitesell
Patrick Whitesell is a prominent American talent agent and entertainment executive, best known as a top leader and co-founder of the global media and talent representation company Endeavor.
-
C.
Andrew Lowe
Andrew Lowe is a film producer known for his work on acclaimed movies such as "Poor Things."
-
D.
Scott Reed
Scott Reed is a computer scientist and machine learning researcher known for his work on deep learning and generative models.
-
E.
Michael McDowell
Michael McDowell was an American novelist and screenwriter best known for his Southern Gothic horror fiction and for writing the screenplay for the film "Beetlejuice."
- 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_69e245af8a88819084f2704f6d265a92 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a74dbea8819085ca84391039e7f7 |
completed | April 29, 2026, 6:38 a.m. |
Created at: April 17, 2026, 6:01 p.m.