Triple
T1725394
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joe Hill |
E37484
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Joe Hill |
E37484
|
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: Joe Hill | Statement: [Joe Hill, name, Joe Hill]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joe Hill Context triple: [Joe Hill, name, Joe Hill]
-
A.
Joe Hill
chosen
Joe Hill is an American author known for his horror and dark fantasy novels and comics, and is the son of writer Stephen King.
-
B.
Jed Harris
Jed Harris was a prominent American theatrical producer and director known for staging influential Broadway productions in the mid-20th century.
-
C.
Dan Jewett
Dan Jewett is an American science teacher known for his brief marriage to billionaire philanthropist and novelist MacKenzie Scott.
-
D.
Samuel Dracutt
Samuel Dracutt was a historical figure after whom the town of Dracut, Massachusetts, was named, likely an early landowner or prominent local settler.
-
E.
Gaiman
Gaiman is a small town in Argentina’s Chubut Province, known for its strong Welsh heritage, traditional tea houses, and distinctive Patagonian landscape.
- 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_69a8861acab88190bb43cde203429399 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa635cad5481908e6c04a230d3b0bb |
completed | March 6, 2026, 5:17 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad8af329a481908cbd3cf351fabfd5 |
completed | March 8, 2026, 2:42 p.m. |
Created at: March 4, 2026, 7:30 p.m.