Triple
T20540986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emily Davis |
E504331
|
entity |
| Predicate | hasFriend |
P8712
|
FINISHED |
| Object | Chris Hartley |
—
|
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 Hartley | Statement: [Emily Davis, hasFriend, Chris Hartley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chris Hartley Context triple: [Emily Davis, hasFriend, Chris Hartley]
-
A.
Chris Hartley
chosen
Chris Hartley is an individual known primarily in relation to Mike Munroe, though publicly available information about him is limited.
-
B.
Chris Hartley
Chris Hartley is a playable protagonist in the horror video game Until Dawn, known for his sarcastic personality and central role in the group’s struggle to survive a deadly night on Blackwood Mountain.
-
C.
Joe Royall
Joe Royall is an individual recognized as a notable bearer of the surname Royall.
-
D.
Chris Haywood
Chris Haywood is an Australian actor known for his extensive work in film, television, and theatre since the 1970s.
-
E.
John Bunn
John Bunn was an American basketball coach and administrator known for his influential roles in college basketball and contributions to the sport’s development.
- 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_69e0b4b476648190bc6019622ae54d3c |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a29224f081908298d104161c5bb9 |
completed | April 20, 2026, 10:02 p.m. |
Created at: April 16, 2026, 11:37 a.m.