Triple
T10583393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philip Seymour Hoffman |
E249791
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Hoffman |
E85402
|
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: Hoffman | Statement: [Philip Seymour Hoffman, familyName, Hoffman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hoffman Context triple: [Philip Seymour Hoffman, familyName, Hoffman]
-
A.
Hoffman
chosen
Hoffman is a common German-origin surname borne by numerous notable individuals across fields such as business, entertainment, science, and politics.
-
B.
Hofmann
Hofmann is a German-language surname borne by numerous notable individuals across fields such as music, science, and the arts.
-
C.
Hoffmann
Hoffmann is a common German surname borne by numerous notable figures in fields such as science, literature, music, and politics.
-
D.
Hoffer
Hoffer is a surname most notably associated with Abram Hoffer, a Canadian psychiatrist known for his work in orthomolecular medicine and niacin therapy for mental illness.
-
E.
William Hoffman
William Hoffman is a relatively common personal name shared by multiple notable individuals across fields such as literature, politics, and the arts.
- 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_69d381c9d3d48190a29ee491e1696a0e |
completed | April 6, 2026, 9:50 a.m. |
| NER | Named-entity recognition | batch_69d52767d2e0819099511e29e254bc34 |
completed | April 7, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d94b820330819090ed70c6ba29b5c2 |
completed | April 10, 2026, 7:12 p.m. |
Created at: April 6, 2026, 12:39 p.m.