Triple
T12378176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UKG |
E295677
|
entity |
| Predicate | product |
P490
|
FINISHED |
| Object | UKG Pro |
E295677
|
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: UKG Pro | Statement: [UKG, product, UKG Pro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: UKG Pro Context triple: [UKG, product, UKG Pro]
-
A.
UKG
chosen
UKG is a U.S.-based technology company specializing in human capital management and workforce management solutions.
-
B.
UKG39
UKG39 is the NUTS 3 statistical region code assigned to the Wolverhampton area in the United Kingdom.
-
C.
UPG
UPG is the IATA airport code for Sultan Hasanuddin International Airport serving Makassar in South Sulawesi, Indonesia.
-
D.
Ug
Ug is a shape-shifting intergalactic bounty hunter featured in the sci-fi horror comedy film "Critters 2: The Main Course."
-
E.
USK
USK is the German Entertainment Software Self-Regulation Body responsible for age rating and classifying video games and other interactive media.
- 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_69d6ad9e653c8190b1473c860ee53dae |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d93fb8d6c081909e8bbbd52c73f29c |
completed | April 10, 2026, 6:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f62ac3c9f081909cd55f966ab6b465 |
completed | May 2, 2026, 4:48 p.m. |
Created at: April 8, 2026, 9:54 p.m.