Triple
T19082176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Martin Noth |
E467058
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Noth |
—
|
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: Noth | Statement: [Martin Noth, familyName, Noth]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Noth Context triple: [Martin Noth, familyName, Noth]
-
A.
Noth
chosen
Noth is a surname most prominently associated with American actor Chris Noth, known for his roles in television series such as "Sex and the City" and "Law & Order."
-
B.
Ynot
Ynot is a film production company known for its work on the acclaimed Mexican romantic drama "Like Water for Chocolate."
-
C.
Nol
Nol is the given name of Lon Nol, the Cambodian military leader and politician who served as Prime Minister and later led the Khmer Republic in the early 1970s.
-
D.
Notsi
Notsi is an Oceanic language spoken in parts of Papua New Guinea, belonging to the Meso-Melanesian branch of the Austronesian language family.
-
E.
Noaea
Noaea is a small genus of flowering plants in the amaranth family Amaranthaceae, native to arid and semi-arid regions of Eurasia and North Africa.
- 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_69d8dd04f4488190b1121cc53ef2bfd6 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e2e9fccc819092c06c5da6f043ac |
completed | April 20, 2026, 8:25 a.m. |
Created at: April 10, 2026, 12:04 p.m.