Triple
T17852027
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Stricker |
E445830
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | John Stricker |
—
|
NE NERFINISHED |
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: John Stricker | Statement: [John Stricker, name, John Stricker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Stricker Context triple: [John Stricker, name, John Stricker]
-
A.
John Stricker
chosen
John Stricker was an American militia officer best known for commanding the Maryland militia at the Battle of North Point during the War of 1812.
-
B.
Warren Berlinger
Warren Berlinger was an American character actor known for his work in film, television, and stage from the 1950s onward.
-
C.
Garrett E. Reisman
Garrett E. Reisman is an American engineer and former NASA astronaut who flew on multiple Space Shuttle missions and completed a long-duration stay aboard the International Space Station.
-
D.
Stephen P. Yokich
Stephen P. Yokich was an American labor leader who played a prominent role in representing and negotiating for autoworkers in the United States.
-
E.
John Beeman
John Beeman was an early Texas settler associated with the pioneering families connected to John Neely Bryan, the founder of Dallas.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b9f26f18819089c9e43250bee6ae |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48fff6c288190a2b5e60b66c03ddc |
completed | April 19, 2026, 8:19 a.m. |
Created at: April 10, 2026, 10:17 a.m.