Triple
T2240773
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mark Owen |
E49389
|
entity |
| Predicate | notableSingle |
P3283
|
FINISHED |
| Object | Clementine |
E3423
|
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: Clementine | Statement: [Mark Owen, notableSingle, Clementine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Clementine Context triple: [Mark Owen, notableSingle, Clementine]
-
A.
Clementine
chosen
Clementine is a feminine given name most famously borne by Clementine Churchill, the wife of British Prime Minister Winston Churchill.
-
B.
Berry
Berry is a historic province in central France known for its rural landscapes, medieval heritage, and traditional French culture.
-
C.
Catherine Apple
Catherine Apple is an editor known for her work on projects involving Luca.
-
D.
Clémentine
Clémentine is a feminine given name of French origin, commonly used in Francophone countries and beyond.
-
E.
Mikan
Mikan is a surname most famously associated with George Mikan, a pioneering American professional basketball player often regarded as the NBA’s first dominant big man.
- 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_69a88aa84bdc819086df50e9c20b301e |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc0bccf688190bd10202a62fdf34e |
completed | March 7, 2026, 6:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae6b0cb4f0819087061434d44dc3a3 |
completed | March 9, 2026, 6:39 a.m. |
Created at: March 4, 2026, 7:47 p.m.