Triple
T19692173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BuddyPress |
E472860
|
entity |
| Predicate | integratesWith |
P1075
|
FINISHED |
| Object | bbPress |
—
|
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: bbPress | Statement: [BuddyPress, integratesWith, bbPress]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: bbPress Context triple: [BuddyPress, integratesWith, bbPress]
-
A.
bbPress
chosen
bbPress is an open-source forum software built as a lightweight, plugin-based extension to WordPress for creating discussion boards and community forums.
-
B.
Foros
Foros is a coastal resort settlement on the southern shore of Crimea, known for its scenic cliffs, beaches, and the landmark Church of the Resurrection overlooking the Black Sea.
-
C.
BuddyPress
BuddyPress is an open-source plugin for WordPress that adds social networking features like user profiles, activity streams, groups, and private messaging to WordPress sites.
-
D.
WordPress
WordPress is a widely used open-source content management system that enables users to create, manage, and publish websites and blogs through a user-friendly, web-based interface.
-
E.
BBS
BBS is the station code used to identify the Brandenburger Tor S-Bahn station in Berlin’s public transit system.
- 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_69d8e515bef88190bc30781aea50537a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e64210cddc8190836faa2996a44457 |
completed | April 20, 2026, 3:11 p.m. |
Created at: April 10, 2026, 1:46 p.m.