Triple
T2166044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Find My iPhone |
E46910
|
entity |
| Predicate | replacedBy |
P101
|
FINISHED |
| Object | Find My |
E46910
|
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: Find My | Statement: [Find My iPhone, replacedBy, Find My]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Find My Context triple: [Find My iPhone, replacedBy, Find My]
-
A.
Find My iPhone
chosen
Find My iPhone is an Apple service that lets users locate, lock, or erase their lost or stolen iOS devices remotely.
-
B.
Findon
Findon is a village in West Sussex, England, situated near the South Downs and known for its rural character and historic charm.
-
C.
Finder
Finder is the primary file management and desktop navigation application for Apple's Macintosh operating systems, providing users with a graphical interface to access and organize files, folders, and drives.
-
D.
Found
Found is an unfinished Pre-Raphaelite painting by Dante Gabriel Rossetti depicting a country drover’s tragic encounter with his former lover, now fallen into prostitution, on a London street.
-
E.
Whereabouts
Whereabouts is a reflective, introspective novel by Jhumpa Lahiri that follows an unnamed woman navigating solitude and everyday life in an unnamed Italian city.
- 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_69a88a184cbc8190877791f6552c2484 |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abbeab223881908aaa2bc4f85329cc |
completed | March 7, 2026, 5:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae58f044b8819092c58022383d3468 |
completed | March 9, 2026, 5:21 a.m. |
Created at: March 4, 2026, 7:45 p.m.