Triple
T20554270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jenna Ortega |
E504674
|
entity |
| Predicate | participatedIn |
P149
|
FINISHED |
| Object | X (2022 film) |
—
|
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: X (2022 film) | Statement: [Jenna Ortega, participatedIn, X (2022 film)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: X (2022 film) Context triple: [Jenna Ortega, participatedIn, X (2022 film)]
-
A.
X (2022 film)
chosen
X (2022 film) is a 2022 American slasher horror movie directed by Ti West, noted for its retro 1970s style and for featuring Jenna Ortega in a prominent role.
-
B.
xXx: Return of Xander Cage
xXx: Return of Xander Cage is a 2017 action film in the xXx franchise that follows extreme athlete-turned-spy Xander Cage as he leads a team on a high-stakes global mission.
-
C.
xXx
xXx is a 2002 action film starring Vin Diesel as an extreme sports athlete recruited by the U.S. government for a high-risk espionage mission.
-
D.
X2
X2 is a film project edited by Academy Award–winning film editor Elliot Graham.
-
E.
X2
X2 is a renowned 4th-dimension steel roller coaster at Six Flags Magic Mountain, famous for its rotating seats, intense drops, and immersive special effects.
- 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_69e0b4b52c048190952b4d0f430813a3 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a5dbe96c8190a278dfefdb4a5c43 |
completed | April 20, 2026, 10:17 p.m. |
Created at: April 16, 2026, 11:38 a.m.