Triple
T13005349
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Simon Stephens |
E322270
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Heisenberg |
E19631
|
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: Heisenberg | Statement: [Simon Stephens, notableWork, Heisenberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Heisenberg Context triple: [Simon Stephens, notableWork, Heisenberg]
-
A.
Heisenberg
Heisenberg is the criminal alias of Walter White, a high school chemistry teacher turned methamphetamine kingpin in the television series "Breaking Bad."
-
B.
Pauli
Pauli was the commonly used name of Pauli Murray, a pioneering American civil rights activist, lawyer, Episcopal priest, and writer whose work influenced both the civil rights and women’s rights movements.
-
C.
Werner Heisenberg
chosen
Werner Heisenberg was a German theoretical physicist best known as a pioneer of quantum mechanics and the originator of the uncertainty principle.
-
D.
Hark Bohm
Hark Bohm is a German actor, director, and screenwriter known for his collaborations with filmmaker Fatih Akin and his contributions to New German Cinema.
-
E.
EINSTEIN
EINSTEIN is a U.S. federal intrusion detection and prevention system used to monitor and protect government agency networks from cyber threats.
- 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_69d807657e8c8190bd9435ee2f823845 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97e9b27ec8190815c40a05b9ba7d0 |
completed | April 10, 2026, 10:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6c109e59481909fc46b152034c6a9 |
completed | May 3, 2026, 3:29 a.m. |
Created at: April 9, 2026, 8:48 p.m.