Triple
T10665480
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BUAP |
E251345
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object | BUAP |
E251345
|
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: BUAP | Statement: [BUAP, shortName, BUAP]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: BUAP Context triple: [BUAP, shortName, BUAP]
-
A.
BUAP
chosen
BUAP is a major public autonomous university based in Puebla, Mexico, known for its wide range of academic programs and research activities.
-
B.
AUB
AUB is a specialist creative arts university in Bournemouth, England, offering practice-based courses in areas such as art, design, media, and performance.
-
C.
BAIR
BAIR is a leading artificial intelligence research lab at the University of California, Berkeley, known for influential work across machine learning, robotics, computer vision, and AI safety.
-
D.
APAS
APAS is a type of androgynous docking mechanism developed for spacecraft to enable compatible, flexible docking between different vehicles.
-
E.
UPSA
UPSA is a public university in Accra, Ghana, specializing in professional, business, and management education.
- 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_69d6aa5b0d2881909584b20efc5877f0 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6f31f87748190bb44db8afa901763 |
completed | April 9, 2026, 12:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d97a9566e08190a92b49ce73963078 |
completed | April 10, 2026, 10:32 p.m. |
Created at: April 8, 2026, 9:08 p.m.