Triple
T20426006
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nagg |
E501001
|
entity |
| Predicate | associatedWork |
P922
|
FINISHED |
| Object | Hamm |
—
|
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: Hamm | Statement: [Nagg, associatedWork, Hamm]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hamm Context triple: [Nagg, associatedWork, Hamm]
-
A.
Hamm
Hamm is a city in North Rhine-Westphalia, Germany, known for its industrial heritage and strategic location in the Ruhr region.
-
B.
Hamm
Hamm is the wisecracking plastic piggy bank toy from the Toy Story film series, known for his sarcastic humor and loyalty to Andy’s other toys.
-
C.
Hamm
Hamm is the surname of American actor Jon Hamm, best known for his role as Don Draper on the television series "Mad Men."
-
D.
Hamm
chosen
Hamm is a central character in Samuel Beckett's play "Endgame," depicted as a blind, wheelchair-bound man who exerts tyrannical control over his servant Clov in a bleak, post-apocalyptic setting.
-
E.
Khamûl
Khamûl is one of the chief Ringwraiths in J.R.R. Tolkien’s legendarium, second in power only to the Witch-king of Angmar.
- 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_69e0b4aa68fc8190b1a14c55575ef04a |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67ba86ed88190bf2d4448d2abcdc7 |
completed | April 20, 2026, 7:16 p.m. |
Created at: April 16, 2026, 11:30 a.m.