Triple
T11728117
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Citadels |
E278825
|
entity |
| Predicate | designer |
P184
|
FINISHED |
| Object | Kit Carlson |
E278825
|
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: Kit Carlson | Statement: [Citadels, designer, Kit Carlson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kit Carlson Context triple: [Citadels, designer, Kit Carlson]
-
A.
Kit Carlson
chosen
Kit Carlson is a game designer best known for creating the popular card game "Citadels."
-
B.
Chris Carlson
Chris Carlson is a notable individual recognized for achievements significant enough to distinguish the name Carlson in public records or discourse.
-
C.
Eric Carlson
Eric Carlson is a notable individual whose name is shared with multiple public figures, including professionals in fields such as architecture and music.
-
D.
Ben Carlson
Ben Carlson is a financial writer and portfolio manager known for his blog and books on investing and personal finance.
-
E.
Ron Carlson
Ron Carlson is an American author and educator known for his acclaimed short stories and novels that often explore everyday lives with humor and emotional depth.
- 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_69d6aaffec6881908bead509e8621742 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a4d80ef881908cab956787ab07fd |
completed | April 10, 2026, 7:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f0198de0708190bc3f6ec2533c8a5b |
completed | April 28, 2026, 2:21 a.m. |
Created at: April 8, 2026, 9:41 p.m.