Triple
T8249554
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UC Berkeley Parallel Computing Laboratory |
E192922
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object |
Par Lab
Par Lab is a research laboratory at UC Berkeley focused on advancing parallel computing systems, software, and applications.
|
E721460
|
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: Par Lab | Statement: [UC Berkeley Parallel Computing Laboratory, shortName, Par Lab]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Par Lab Context triple: [UC Berkeley Parallel Computing Laboratory, shortName, Par Lab]
-
A.
Labro
Labro is a small medieval hilltop village in central Italy known for its well-preserved historic architecture and scenic views over Lake Piediluco.
-
B.
Pal
Pal is an Indian surname notably borne by Bipin Chandra Pal, a prominent nationalist leader in the Indian independence movement.
-
C.
Labo
Labo is a municipality in the Philippine province of Camarines Norte known for its agricultural economy and natural attractions such as caves, waterfalls, and mineral resources.
-
D.
Parl
Parl is the commonly used abbreviation for the Parliament of Singapore, the country's unicameral legislative body.
-
E.
Premo
Premo is the nickname of DJ Premier, a highly influential American hip-hop producer and DJ known for his gritty, sample-based boom-bap sound.
- 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: Par Lab Triple: [UC Berkeley Parallel Computing Laboratory, shortName, Par Lab]
Generated description
Par Lab is a research laboratory at UC Berkeley focused on advancing parallel computing systems, software, and applications.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Par Lab Target entity description: Par Lab is a research laboratory at UC Berkeley focused on advancing parallel computing systems, software, and applications.
-
A.
Labro
Labro is a small medieval hilltop village in central Italy known for its well-preserved historic architecture and scenic views over Lake Piediluco.
-
B.
Pal
Pal is an Indian surname notably borne by Bipin Chandra Pal, a prominent nationalist leader in the Indian independence movement.
-
C.
Labo
Labo is a municipality in the Philippine province of Camarines Norte known for its agricultural economy and natural attractions such as caves, waterfalls, and mineral resources.
-
D.
Parl
Parl is the commonly used abbreviation for the Parliament of Singapore, the country's unicameral legislative body.
-
E.
Premo
Premo is the nickname of DJ Premier, a highly influential American hip-hop producer and DJ known for his gritty, sample-based boom-bap sound.
- 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_69ca82de7b8c81908d8106f8a53cff9b |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb78c817708190ad1c364e12083d26 |
completed | March 31, 2026, 7:33 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd353888208190941d1c0b7b911cdd |
completed | April 1, 2026, 3:09 p.m. |
| NEDg | Description generation | batch_69cd37a71af481909e82aa29ae558c4a |
completed | April 1, 2026, 3:20 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cd4ef034ec8190a4229b21e6088c79 |
completed | April 1, 2026, 4:59 p.m. |
Created at: March 30, 2026, 5:48 p.m.