Triple
T20083443
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manassas |
E500061
|
entity |
| Predicate | member |
P10
|
FINISHED |
| Object | Dallas Taylor |
—
|
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: Dallas Taylor | Statement: [Manassas, member, Dallas Taylor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dallas Taylor Context triple: [Manassas, member, Dallas Taylor]
-
A.
Dallas Taylor
chosen
Dallas Taylor was an American rock drummer best known for his work with Crosby, Stills, Nash & Young during the late 1960s and early 1970s.
-
B.
Dallas Taylor
Dallas Taylor is a music producer known for his work on the track "Déjà Vu."
-
C.
Orville Mohler
Orville Mohler was an American college football player and coach, best known for his time as a quarterback at the University of Southern California (USC) in the early 1930s.
-
D.
Rob Morgan
Rob Morgan is an American character actor known for his roles in films like "Mudbound" and "Just Mercy" and in television series such as Marvel’s Netflix shows and "Stranger Things."
-
E.
Kevin Dobson
Kevin Dobson was an American actor best known for his television roles in series such as Kojak and Knots Landing.
- 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_69da627770948190997f486f9a2e370f |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6655946f48190a6b4cb13ea4e212a |
completed | April 20, 2026, 5:41 p.m. |
Created at: April 11, 2026, 3:41 p.m.