Triple
T13419335
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harry Callahan |
E313297
|
entity |
| Predicate | createdBy |
P806
|
FINISHED |
| Object | R. M. Fink |
E994628
|
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: R. M. Fink | Statement: [Harry Callahan, createdBy, R. M. Fink]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: R. M. Fink Context triple: [Harry Callahan, createdBy, R. M. Fink]
-
A.
R. M. Fink
chosen
R. M. Fink is a screenwriter best known for co-writing the influential 1971 crime film "Dirty Harry."
-
B.
Carlo H. Séquin
Carlo H. Séquin is a Swiss-American computer scientist and UC Berkeley professor known for his pioneering work in VLSI design and computer architecture, as well as his contributions to geometric modeling and computer graphics.
-
C.
Ray W. Bliss
Ray W. Bliss was a prominent American physician and U.S. Army medical officer whose service and leadership in military medicine led to a major Army health center being named in his honor.
-
D.
John Eames
John Eames is a central young clerk and romantic figure in Anthony Trollope’s Barsetshire novels, notably portrayed as an earnest but socially awkward suitor.
-
E.
John Knill
John Knill is a distinguished geologist recognized for his significant contributions to the field, as evidenced by honors such as the William Smith Medal.
- 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_69d806ad0c44819088833ae1ec9e9690 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaeb98e808190948013e8f24779c6 |
completed | April 12, 2026, 2:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f73082a2548190aefc0f202b84165c |
completed | May 3, 2026, 11:24 a.m. |
Created at: April 9, 2026, 9:39 p.m.