Triple
T22028183
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Linphone |
E544017
|
entity |
| Predicate | hasComponent |
P35
|
FINISHED |
| Object | Liblinphone |
—
|
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: Liblinphone | Statement: [Linphone, hasComponent, Liblinphone]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Liblinphone Context triple: [Linphone, hasComponent, Liblinphone]
-
A.
Linphone
chosen
Linphone is an open-source Voice over IP (VoIP) softphone application that supports audio and video calls, messaging, and encryption across multiple platforms.
-
B.
Jitsi
Jitsi is an open-source, cross-platform suite of real-time voice, video, and chat communication tools focused on secure, encrypted conferencing.
-
C.
Telephony Manager
Telephony Manager is an Android framework service that provides APIs for accessing and managing telephony-related information and operations such as network status, SIM details, and call state.
-
D.
GlobalSIP
GlobalSIP is an IEEE-sponsored international conference focused on advances and research in signal and information processing.
-
E.
SIP
SIP is a Unicode supplementary plane that contains additional CJK ideographs beyond those in the Basic Multilingual Plane.
- 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_69e11e2e8ea4819084210fe06d3a1b8d |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f127cdf5c08190ac804664d6e56fe2 |
completed | April 28, 2026, 9:34 p.m. |
Created at: April 16, 2026, 8:24 p.m.