Triple
T7843552
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leo Gordon |
E181862
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Maverick (TV series) |
E188689
|
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: Maverick (TV series) | Statement: [Leo Gordon, notableWork, Maverick (TV series)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maverick (TV series) Context triple: [Leo Gordon, notableWork, Maverick (TV series)]
-
A.
Maverick
chosen
Maverick is a classic American Western comedy television series that aired in the late 1950s, following the adventures of charming, poker-playing gambler Bret Maverick and his relatives.
-
B.
Maverick
Maverick is a political nickname for U.S. Senator John McCain, reflecting his reputation for independence and willingness to break with his party.
-
C.
Maverick
Maverick is the daring U.S. Navy fighter pilot Pete "Maverick" Mitchell, the iconic lead character of the Top Gun film series.
-
D.
Maverick
Maverick is a high-speed steel roller coaster at Cedar Point in Ohio, renowned for its intense launches, inversions, and twisted track layout.
-
E.
Maverick
Maverick is an MBTA subway station on Boston’s Blue Line serving the East Boston neighborhood.
- 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_69ca8285d6488190a95d4c02d7354b53 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb163c72248190b53bc53980e8ac0f |
completed | March 31, 2026, 12:33 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb5aded4048190b18604963784352c |
completed | March 31, 2026, 5:25 a.m. |
Created at: March 30, 2026, 4:48 p.m.