Triple
T5016862
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apple ecosystem |
E112757
|
entity |
| Predicate | includesApplication |
P14571
|
FINISHED |
| Object | Pages |
E184250
|
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: Pages | Statement: [Apple ecosystem, includesApplication, Pages]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pages Context triple: [Apple ecosystem, includesApplication, Pages]
-
A.
Pages
chosen
Pages is Apple's word processing and page layout application, part of the iWork productivity suite for macOS and iOS.
-
B.
Page
Page is a common English surname borne by numerous notable individuals across fields such as technology, entertainment, and politics.
-
C.
The Pagemaster
The Pagemaster is a 1994 live-action/animated fantasy adventure film in which a timid boy is transported into a magical library world where classic literary characters help him overcome his fears.
-
D.
The Paper
The Paper is a 1994 American comedy-drama film directed by Ron Howard that follows the hectic, deadline-driven day at a New York City tabloid newspaper.
-
E.
PAG
PAG is the stock ticker and common abbreviation for Penske Automotive Group, a large international transportation services company specializing in automotive and commercial truck dealerships.
- 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_69bd4434acb8819086679dbeccc2fe54 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd77c9fc7c8190b165a5cfd5889ba8 |
completed | March 20, 2026, 4:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be9278421c8190b142466c099c7d1c |
completed | March 21, 2026, 12:43 p.m. |
Created at: March 20, 2026, 1:35 p.m.