Triple
T20146981
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Where You Live |
E491326
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object | Taken |
—
|
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: Taken | Statement: [Where You Live, hasTrack, Taken]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Taken Context triple: [Where You Live, hasTrack, Taken]
-
A.
Taken
Taken is a 2008 action thriller film in which Liam Neeson plays a former CIA operative who relentlessly hunts down his daughter's kidnappers in Paris.
-
B.
Taken
chosen
Taken is a science fiction television miniseries that explores multiple generations of human encounters with extraterrestrials and government conspiracies.
-
C.
Stolen
Stolen is a 2012 action thriller film starring Nicolas Cage as a former thief racing against time to rescue his kidnapped daughter.
-
D.
Stolen
"Stolen" is a song by British-Indian singer Jay Sean that blends R&B and pop influences and helped establish his early mainstream success.
-
E.
Stolen
"Stolen" is a suspense thriller novel by Tess Gerritsen that follows a woman whose identity and life are suddenly erased, plunging her into a dangerous conspiracy.
- 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_69da6265f8f0819080b29c752a574088 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e6679f43bc8190a1cd4768b3e87505 |
completed | April 20, 2026, 5:51 p.m. |
Created at: April 11, 2026, 11:33 p.m.