Triple
T23515527
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Chief |
E574351
|
entity |
| Predicate | hasColleague |
P398
|
FINISHED |
| Object | Agent 13 |
—
|
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: Agent 13 | Statement: [The Chief, hasColleague, Agent 13]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Agent 13 Context triple: [The Chief, hasColleague, Agent 13]
-
A.
Agent 13
chosen
Agent 13 is the codename of Sharon Carter, a highly skilled S.H.I.E.L.D. operative and frequent ally of Captain America in Marvel Comics.
-
B.
Agent 13
Agent 13 is an unproduced film script centered on a mysterious spy character, known primarily within industry and fan circles for its unrealized cinematic potential.
-
C.
Agent 13
Agent 13 is the covert alias used by James Wilkinson, a character known as a skilled undercover operative in the Marvel universe.
-
D.
Agent 86
Agent 86 is the bumbling yet resourceful secret agent protagonist of the classic satirical spy television series "Get Smart."
-
E.
Agent 0054
Agent 0054 is the exaggerated secret-agent persona played by comedian Kevin Hart in his stand-up concert film "Kevin Hart: What Now?".
- 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_69e245bb3dcc8190ba9a2b35972b58d0 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1aa81ab4c8190b85c8f80754020ea |
completed | April 29, 2026, 6:51 a.m. |
Created at: April 17, 2026, 6:08 p.m.