Triple
T16125385
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dana Andrews |
E391255
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Andrews |
E440925
|
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: Andrews | Statement: [Dana Andrews, familyName, Andrews]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Andrews Context triple: [Dana Andrews, familyName, Andrews]
-
A.
Andrews
Andrews is the middle name of Thomas A. Hendricks, the 21st vice president of the United States.
-
B.
Andrews
Andrews is a small city in West Texas known primarily for its role in the region’s oil and gas industry.
-
C.
Andrews
chosen
Andrews is a common English-language surname borne by numerous notable figures across fields such as the military, politics, science, and the arts.
-
D.
Andrews
Andrews is the middle name of American experimental physicist and Nobel laureate Robert A. Millikan.
-
E.
David Andrews
David Andrews is an American character actor known for his roles in films such as "Graveyard Shift," "Apollo 13," and "Fight Club," as well as numerous television appearances.
- 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_69d87f1bb0988190b490d273dbf3fd03 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e2020408a88190bf3dfc893d577c55 |
completed | April 17, 2026, 9:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff2abf9b08190a375abc842a0e7d0 |
completed | May 10, 2026, 2:51 a.m. |
Created at: April 10, 2026, 5 a.m.