Triple
T13202468
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Drunkenness of Noah |
E314274
|
entity |
| Predicate | involvesCharacter |
P15562
|
FINISHED |
| Object | Ham |
E381221
|
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: Ham | Statement: [Drunkenness of Noah, involvesCharacter, Ham]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ham Context triple: [Drunkenness of Noah, involvesCharacter, Ham]
-
A.
Ham
Ham is a municipality in the Belgian province of Limburg, known for its rural character and location in the Flemish Region.
-
B.
Ham
Ham is a suburban riverside district in southwest London, England, known for its historic houses, green spaces, and proximity to the River Thames.
-
C.
Ham
Ham is a small town in the Somme department of northern France, known historically for its medieval fortress and strategic location.
-
D.
Ham
chosen
Ham is a biblical figure known as one of Noah’s sons and a progenitor of several ancient peoples mentioned in the Hebrew Bible.
-
E.
HAM
HAM is the IATA airport code for Hamburg Airport, the international airport serving the city of Hamburg, Germany.
- 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_69d806aee7308190b70a237ba2a6e3e1 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98c9961a48190a1157df47f59b7af |
completed | April 10, 2026, 11:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6f60cf610819098d0c45989e3f9cf |
completed | May 3, 2026, 7:15 a.m. |
Created at: April 9, 2026, 9:16 p.m.