Triple
T3167572
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apple iChat |
E66247
|
entity |
| Predicate | marketingName |
P11546
|
FINISHED |
| Object | iChat |
E66247
|
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: iChat | Statement: [Apple iChat, marketingName, iChat]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: iChat Context triple: [Apple iChat, marketingName, iChat]
-
A.
Apple iChat
chosen
Apple iChat is Apple’s former instant messaging and video chat application for macOS that integrated AIM, Jabber, and later FaceTime-style communication features.
-
B.
AOL Instant Messenger
AOL Instant Messenger was a pioneering late-1990s and early-2000s instant messaging service that popularized online chat and status-based communication for mainstream internet users.
-
C.
ICQ
ICQ is one of the earliest popular internet instant messaging services, widely used in the late 1990s and early 2000s.
-
D.
iMessage
iMessage is Apple’s encrypted instant messaging service that enables text, media, and rich communication features between users of Apple devices.
-
E.
Chatterbug
Chatterbug is an online language-learning platform that offers live tutoring and interactive exercises to help users practice and improve foreign language skills.
- 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_69ad8585d7988190af37365331093ccd |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada6457acc8190b2b9acbd1cfcdb91 |
completed | March 8, 2026, 4:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b235e108cc81909d5733bd00cb0bee |
completed | March 12, 2026, 3:41 a.m. |
Created at: March 8, 2026, 3:06 p.m.