Triple
T16238044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quentin |
E394165
|
entity |
| Predicate | shortForm |
P43
|
FINISHED |
| Object | Quinn |
unclear NED1
|
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: Quinn | Statement: [Quentin, shortForm, Quinn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Quinn Context triple: [Quentin, shortForm, Quinn]
-
A.
Quinn
Quinn is the romantic partner associated with the character Sam Hanna from the television series NCIS: Los Angeles.
-
B.
Quinn
Quinn is the central protagonist of the television series "Mad Dogs," around whom the show's primary conflicts and storylines revolve.
-
C.
Quinn
Quinn is a small rural town located in Pennington County, South Dakota.
-
D.
Quinn
Quinn is a fictional character portrayed by actor Marton Csokas, known for his intense and often complex roles in film and television.
-
E.
Quinn
Quinn is a surname of Irish origin commonly borne by individuals such as American football coach Dan Quinn.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
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_69d87f2171208190951025e526947816 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2455c7a3c81909e3b42edf03be43e |
completed | April 17, 2026, 2:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a000edaf76c8190acc01f58845e570a |
completed | May 10, 2026, 4:51 a.m. |
Created at: April 10, 2026, 5:04 a.m.