Triple
T6719493
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charlie Watts |
E153358
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Watts |
E167722
|
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: Watts | Statement: [Charlie Watts, familyName, Watts]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Watts Context triple: [Charlie Watts, familyName, Watts]
-
A.
Watts
chosen
Watts is a surname of English and Scottish origin, often associated with notable figures in science, arts, and public life.
-
B.
Watts
Watts is a historic neighborhood in South Los Angeles known for its cultural significance, diverse community, and landmarks such as the Watts Towers.
-
C.
Watts, Los Angeles
Watts is a historically significant neighborhood in South Los Angeles known for its African American cultural heritage, the Watts Towers art landmark, and the 1965 Watts riots.
-
D.
Compton
Compton is a common English surname borne by various notable individuals in science, politics, and the arts.
-
E.
Marshall
Marshall is a 2017 biographical legal drama film about a young Thurgood Marshall, directed by Reginald Hudlin and starring Chadwick Boseman.
- 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_69c68809b4608190a2509ddb5ab87f05 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d135d27c819088c45839ad0e7bab |
completed | March 27, 2026, 6:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7009f1e208190891c4542a6c613ac |
completed | March 27, 2026, 10:11 p.m. |
Created at: March 27, 2026, 2:07 p.m.