Triple
T9997600
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jenno Topping |
E197238
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Spy (2015 film) |
E714543
|
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: Spy (2015 film) | Statement: [Jenno Topping, notableWork, Spy (2015 film)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Spy (2015 film) Context triple: [Jenno Topping, notableWork, Spy (2015 film)]
-
A.
Spy (2015 film)
Spy (2015 film) is an action-comedy movie starring Melissa McCarthy as a CIA analyst who goes undercover to prevent a global disaster.
-
B.
SPY
SPY is the SPDR S&P 500 ETF, a widely traded fund that tracks the performance of the S&P 500 stock market index.
-
C.
American Spy
"American Spy" is a memoir by former CIA officer and Watergate conspirator E. Howard Hunt, recounting his clandestine operations and career in U.S. intelligence.
-
D.
Spy
chosen
Spy is a 2015 action-comedy film starring Melissa McCarthy as a desk-bound CIA analyst who goes undercover to infiltrate the world of deadly arms dealers.
-
E.
Spy Game
Spy Game is a 2001 espionage thriller film directed by Tony Scott, starring Robert Redford and Brad Pitt as CIA operatives navigating a high-stakes rescue mission amid Cold War-era intrigue.
- 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_69ca82f3b61c81908ecc2c1c96dbc2e4 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdcc8aa1a881909879a694496f11a5 |
completed | April 2, 2026, 1:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d258439fe88190b17da69f542ecf61 |
completed | April 5, 2026, 12:40 p.m. |
Created at: March 30, 2026, 8:51 p.m.