Triple
T3682144
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Connelly |
E78136
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Michael Connelly |
E78136
|
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: Michael Connelly | Statement: [Michael Connelly, name, Michael Connelly]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Connelly Context triple: [Michael Connelly, name, Michael Connelly]
-
A.
Michael Connelly
chosen
Michael Connelly is a bestselling American crime fiction author best known for his Harry Bosch and Lincoln Lawyer series.
-
B.
Lee Child
Lee Child is a British thriller author best known for creating the Jack Reacher series of novels.
-
C.
Nathan Barr
Nathan Barr is an American film and television composer known for his atmospheric scores on projects ranging from horror films to acclaimed series like True Blood and The Americans.
-
D.
Harry Hart
Harry Hart is a suave, highly skilled British secret agent and mentor figure in the Kingsman film series.
-
E.
James Ellroy
James Ellroy is an American crime fiction writer renowned for his dark, intricately plotted L.A. Quartet novels and his stylized, staccato prose.
- 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_69ad85e18c1c8190be8aafb227f39f48 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc492aed481909e8986378ad283fc |
completed | March 8, 2026, 6:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4c3b306c081909b3857daa4f97ce2 |
completed | March 14, 2026, 2:10 a.m. |
Created at: March 8, 2026, 3:25 p.m.