Triple
T9723304
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emily Charlton |
E235535
|
entity |
| Predicate | hasColleague |
P398
|
FINISHED |
| Object | Andy Sachs |
E149889
|
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: Andy Sachs | Statement: [Emily Charlton, hasColleague, Andy Sachs]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Andy Sachs Context triple: [Emily Charlton, hasColleague, Andy Sachs]
-
A.
Andrea Sachs
chosen
Andrea Sachs is the ambitious young journalist who becomes the overworked assistant to powerful fashion editor Miranda Priestly in "The Devil Wears Prada."
-
B.
Eli Sachs
Eli Sachs is the central character in the television series "Dads," around whom the show's comedic storylines and family dynamics revolve.
-
C.
Alex Saks
Alex Saks is a film producer known for her work on independent and studio-backed feature films.
-
D.
Andrew Sachs
Andrew Sachs was a British actor best known for his comedic role as the hapless waiter Manuel in the classic sitcom "Fawlty Towers."
-
E.
Andrew Mondshein
Andrew Mondshein is an American film editor known for his work on acclaimed movies such as "Ma Rainey's Black Bottom" and "The Sixth Sense."
- 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_69ca84d0123c819096f9dc3b6abb0881 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9e75abd48190a6e6679ec51496e8 |
completed | April 1, 2026, 10:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1afb089e48190a14ed0c0f81872c7 |
completed | April 5, 2026, 12:41 a.m. |
Created at: March 30, 2026, 8:20 p.m.