Triple
T10174538
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LaShawn Daniels |
E235816
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Daniels |
E102532
|
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: Daniels | Statement: [LaShawn Daniels, familyName, Daniels]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daniels Context triple: [LaShawn Daniels, familyName, Daniels]
-
A.
Daniels
chosen
Daniels is a common English-language surname borne by numerous notable individuals across politics, sports, entertainment, and other fields.
-
B.
McDaniels
McDaniels is a surname most notably associated with American professional basketball players, including Jalen McDaniels.
-
C.
Denis
Denis is a masculine given name of French origin, famously borne by the Enlightenment philosopher Denis Diderot.
-
D.
Denis
Denis was a key member of Les Nabis, a late 19th-century group of avant-garde French artists who helped pioneer Symbolism and modernist painting.
-
E.
Dannel
Dannel is the given name of Dannel P. Malloy, an American politician who served as the 88th governor of Connecticut.
- 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_69ca84d1d5f88190ab878a1021ecff68 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdecd26a8c8190a391b9d5e47ebb72 |
completed | April 2, 2026, 4:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d3011742b48190bc8b8b6ba03c32b0 |
completed | April 6, 2026, 12:40 a.m. |
Created at: March 30, 2026, 9:11 p.m.