Triple
T13320013
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lisa Su |
E317289
|
entity |
| Predicate | boardMemberOf |
P10
|
FINISHED |
| Object | Cisco Systems |
E5543
|
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: Cisco Systems | Statement: [Lisa Su, boardMemberOf, Cisco Systems]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cisco Systems Context triple: [Lisa Su, boardMemberOf, Cisco Systems]
-
A.
Cisco Systems
chosen
Cisco Systems is a multinational technology conglomerate best known for designing and selling networking hardware, software, and telecommunications equipment used worldwide.
-
B.
3Com
3Com was an American digital electronics and networking company best known for its Ethernet and network interface products before being acquired by Hewlett-Packard.
-
C.
Juniper Networks
Juniper Networks is a multinational networking and cybersecurity company known for its high-performance routers, switches, and related infrastructure solutions for service providers and enterprises.
-
D.
Arista Networks
Arista Networks is a cloud networking company known for its high-performance data center switches and software-driven network solutions.
-
E.
Ubiquiti Networks
Ubiquiti Networks is a technology company that designs and manufactures networking and wireless communication products for service providers and enterprises worldwide.
- 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_69d806b4d62c81908d4ced1665414be5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d990faa95481908a7fd297959c062e |
completed | April 11, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f716ee695c81909ffeeb0901ee66c1 |
completed | May 3, 2026, 9:35 a.m. |
Created at: April 9, 2026, 9:29 p.m.