Triple
T15747881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Drew Fuller |
E381765
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Drew Fuller |
E381765
|
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: Drew Fuller | Statement: [Drew Fuller, name, Drew Fuller]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Drew Fuller Context triple: [Drew Fuller, name, Drew Fuller]
-
A.
Drew Fuller
chosen
Drew Fuller is an American actor and former model best known for his role as Chris Halliwell on the television series "Charmed."
-
B.
Drew Pearce
Drew Pearce is a British screenwriter and filmmaker known for his work on major action and superhero films such as Iron Man 3 and Mission: Impossible – Rogue Nation.
-
C.
Drew Sheehan
Drew Sheehan is a character in the television series "Mare of Easttown," known as the young grandson of the main character, Mare Sheehan.
-
D.
Jacob Fuller
Jacob Fuller is a former pastor and widowed father who becomes entangled in a violent, supernatural ordeal while trying to protect his family in the horror-crime story "From Dusk Till Dawn."
-
E.
Drew Hansen
Drew Hansen is an American lawyer, author, and Democratic politician who has served in the Washington State Legislature.
- 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_69d86d9e6b44819085d1f6a969ecb74c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0502d72008190b4d13a6b3a12e467 |
completed | April 16, 2026, 2:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff8309cba881909579ee5a62b3aa31 |
completed | May 9, 2026, 6:55 p.m. |
Created at: April 10, 2026, 4:46 a.m.