Triple
T11670039
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Weapon X |
E277352
|
entity |
| Predicate | notableSubject |
P4941
|
FINISHED |
| Object | Maverick |
E847620
|
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 | Statement: [Weapon X, notableSubject, Maverick]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maverick Context triple: [Weapon X, notableSubject, Maverick]
-
A.
Maverick
Maverick is a political nickname for U.S. Senator John McCain, reflecting his reputation for independence and willingness to break with his party.
-
B.
Maverick
chosen
Maverick is the codename used by Chris Bradley, a minor Marvel Comics character associated with the X-Men universe who possesses mutant electrical powers.
-
C.
Maverick
Maverick is a high-speed steel roller coaster at Cedar Point in Ohio, renowned for its intense launches, inversions, and twisted track layout.
-
D.
Maverick
Maverick is a cigarette brand known for its budget-friendly positioning within the U.S. tobacco market.
-
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_69d6aafd0a448190b44da30af8c6c519 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a44264c08190ba1a4a5bcdc9367b |
completed | April 10, 2026, 7:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef13c3ea648190ae18cd2869be74ad |
completed | April 27, 2026, 7:44 a.m. |
Created at: April 8, 2026, 9:39 p.m.