Triple
T20661291
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rage |
E507764
|
entity |
| Predicate | originalTitle |
P65
|
FINISHED |
| Object | Rage |
—
|
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: Rage | Statement: [Rage, originalTitle, Rage]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rage Context triple: [Rage, originalTitle, Rage]
-
A.
Rage
Rage is a nonfiction book by investigative journalist Bob Woodward that examines the Trump presidency through interviews, insider accounts, and analysis of key events.
-
B.
Rage
Rage is a post-apocalyptic first-person shooter video game developed by id Software, known for its advanced graphics technology and vehicular combat elements.
-
C.
Rage
Rage is a historical adventure novel by Wilbur Smith that continues the saga of the Courtney family against the backdrop of apartheid-era South Africa.
-
D.
Rage
Rage is a psychological horror novel by Stephen King, originally published under the pseudonym Richard Bachman, that follows a troubled high school student who takes his class hostage.
-
E.
Rage
Rage is a steel roller coaster at Adventure Island known for its steep drops and intense inversions.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
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_69e0b4c059bc81908ea762cd73ea4424 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6b2f16adc8190b2b9a69586fa7444 |
completed | April 20, 2026, 11:12 p.m. |
Created at: April 16, 2026, 11:44 a.m.