Triple
T1793584
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IBM Tivoli management software |
E39552
|
entity |
| Predicate | brand |
P1500
|
FINISHED |
| Object |
Tivoli
Tivoli is an IBM software brand known for its enterprise systems management and monitoring solutions.
|
E200593
|
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: Tivoli | Statement: [IBM Tivoli management software, brand, Tivoli]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tivoli Context triple: [IBM Tivoli management software, brand, Tivoli]
-
A.
Tivoli
Tivoli is an Italian hill town east of Rome renowned for its historic villas and gardens, including Emperor Hadrian’s vast imperial retreat, Hadrian’s Villa.
-
B.
TivoliVredenburg
TivoliVredenburg is a large, modern music complex and cultural venue in Utrecht, Netherlands, known for its multiple concert halls and diverse live performances.
-
C.
Belvedere
Belvedere is an affluent, scenic waterfront city in Marin County, California, known for its views of San Francisco Bay and upscale residential character.
-
D.
Tivoli, Italy
Tivoli, Italy is a historic town near Rome renowned for its ancient villas, spectacular gardens, and scenic waterfalls.
-
E.
Havelterberg
Havelterberg is a modest hill and natural area in the Dutch province of Drenthe, known for its scenic landscapes and prehistoric burial mounds.
- 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: Tivoli Triple: [IBM Tivoli management software, brand, Tivoli]
Generated description
Tivoli is an IBM software brand known for its enterprise systems management and monitoring solutions.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tivoli Target entity description: Tivoli is an IBM software brand known for its enterprise systems management and monitoring solutions.
-
A.
Tivoli
Tivoli is an Italian hill town east of Rome renowned for its historic villas and gardens, including Emperor Hadrian’s vast imperial retreat, Hadrian’s Villa.
-
B.
TivoliVredenburg
TivoliVredenburg is a large, modern music complex and cultural venue in Utrecht, Netherlands, known for its multiple concert halls and diverse live performances.
-
C.
Belvedere
Belvedere is an affluent, scenic waterfront city in Marin County, California, known for its views of San Francisco Bay and upscale residential character.
-
D.
Tivoli, Italy
Tivoli, Italy is a historic town near Rome renowned for its ancient villas, spectacular gardens, and scenic waterfalls.
-
E.
Havelterberg
Havelterberg is a modest hill and natural area in the Dutch province of Drenthe, known for its scenic landscapes and prehistoric burial mounds.
- 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_69a88631854081909723959921e45c2b |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa653c4c148190bfe6ac017ecbf695 |
completed | March 6, 2026, 5:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adb5d26afc81909675064289d3a5b8 |
completed | March 8, 2026, 5:45 p.m. |
| NEDg | Description generation | batch_69adb69b142c81909dd8bd40e8e440ad |
completed | March 8, 2026, 5:49 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adb8bac99081908cf126d42c609559 |
completed | March 8, 2026, 5:58 p.m. |
Created at: March 4, 2026, 7:32 p.m.