Triple
T21218977
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Universitas Pekalongan |
E522913
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object |
UNIKAL
UNIKAL is the commonly used abbreviation for Universitas Pekalongan, a higher education institution located in Pekalongan, Indonesia.
|
E1471329
|
NE FINISHED |
How this triple was built (4 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: UNIKAL | Statement: [Universitas Pekalongan, shortName, UNIKAL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: UNIKAL Context triple: [Universitas Pekalongan, shortName, UNIKAL]
-
A.
UNIKA
UNIKA is the commonly used abbreviation for Soegijapranata Catholic University, a private Catholic higher education institution in Indonesia.
-
B.
Unic
Unic was a French manufacturer of commercial vehicles, particularly trucks and buses, that later became part of the Iveco group through a merger.
-
C.
Unieqav
Unieqav is an experimental electronic music album by German sound artist Alva Noto, known for its minimalist, glitch-infused sonic textures and immersive ambient compositions.
-
D.
Omunique
Omunique is a character appearing in the work "First Sunday," likely contributing to its central comedic and narrative elements.
-
E.
uniq
uniq is a GNU Core Utilities command-line tool that filters or reports repeated lines in sorted text input.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: UNIKAL Triple: [Universitas Pekalongan, shortName, UNIKAL]
Generated description
UNIKAL is the commonly used abbreviation for Universitas Pekalongan, a higher education institution located in Pekalongan, Indonesia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: UNIKAL Target entity description: UNIKAL is the commonly used abbreviation for Universitas Pekalongan, a higher education institution located in Pekalongan, Indonesia.
-
A.
UNIKA
UNIKA is the commonly used abbreviation for Soegijapranata Catholic University, a private Catholic higher education institution in Indonesia.
-
B.
Unic
Unic was a French manufacturer of commercial vehicles, particularly trucks and buses, that later became part of the Iveco group through a merger.
-
C.
Unieqav
Unieqav is an experimental electronic music album by German sound artist Alva Noto, known for its minimalist, glitch-infused sonic textures and immersive ambient compositions.
-
D.
Omunique
Omunique is a character appearing in the work "First Sunday," likely contributing to its central comedic and narrative elements.
-
E.
uniq
uniq is a GNU Core Utilities command-line tool that filters or reports repeated lines in sorted text input.
- F. None of above. chosen
Provenance (5 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_69e0b511ed84819099b449b4a111085c |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e73476d93481909c6c99dcc0b16123 |
completed | April 21, 2026, 8:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a097edb6de4819094cf7a50670afdfa |
completed | May 17, 2026, 8:39 a.m. |
| NEDg | Description generation | batch_6a097f5016348190aeb01856a5c57b41 |
completed | May 17, 2026, 8:41 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a097fe399048190a1b29f16d8e46d8d |
completed | May 17, 2026, 8:44 a.m. |
Created at: April 16, 2026, 3:42 p.m.