Triple

T15364137
Position Surface form Disambiguated ID Type / Status
Subject UniFI E367365 entity
Predicate shortName P43 FINISHED
Object UniFI E367365 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: UniFI | Statement: [UniFI, shortName, UniFI]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: UniFI
Context triple: [UniFI, shortName, UniFI]
  • A. UniFI chosen
    UniFI is the commonly used abbreviation for the University of Florence, a major public research university in Florence, Italy.
  • B. Ubiquiti Networks
    Ubiquiti Networks is a technology company that designs and manufactures networking and wireless communication products for service providers and enterprises worldwide.
  • C. WiFS
    WiFS is a wide-field imaging sensor used on Indian Remote Sensing satellites to capture moderate-resolution, large-area Earth observation data for applications like agriculture and land-use monitoring.
  • D. VoWiFi
    VoWiFi (Voice over Wi-Fi) is a technology that allows mobile voice calls and texts to be carried over Wi-Fi networks instead of traditional cellular networks, improving indoor coverage and call quality.
  • E. Cisco Meraki
    Cisco Meraki is a cloud-managed IT platform that provides centralized management for wireless, switching, security, and other network devices.
  • 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_69d85a1483788190ad93c2748e8af34b completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e497de48190be249b110999ec5c completed April 16, 2026, 1:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff0b4cc39c81908a0aff959352f6d5 completed May 9, 2026, 10:24 a.m.
Created at: April 10, 2026, 3:18 a.m.