Triple
T30354267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Huny |
E772101
|
entity |
| Predicate | hasSuccessorRelationship |
P53377
|
FINISHED |
| Object | predecessor of Sneferu |
—
|
LITERAL 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: predecessor of Sneferu | Statement: [Huny, hasSuccessorRelationship, predecessor of Sneferu]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSuccessorRelationship Context triple: [Huny, hasSuccessorRelationship, predecessor of Sneferu]
-
A.
successorRelationship
chosen
Indicates a relationship where one entity directly follows or replaces another in a sequence, order, or role.
-
B.
isSuccessorTo
Indicates that one entity directly follows another in an ordered sequence, coming immediately after it.
-
C.
predecessorRelationship
Indicates that one entity comes before another in an ordered sequence, chain, or lineage, serving as its prior or earlier counterpart.
-
D.
hasSuccessorShip
Indicates that one entity is the ship that follows or replaces another ship in a sequence or lineage.
-
E.
hasSuccessorUsers
Indicates that one user or set of users is followed or replaced by another user or set of users in a sequence or succession.
- F. None of above.
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_69f2248c6f5c8190a6177842bf791a3c |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fe08d2b2e48190ac7be6d62d4a44a3 |
completed | May 8, 2026, 4:01 p.m. |
| PD | Predicate disambiguation | batch_69fe06cd3af08190ae25de0dc0cdd573 |
completed | May 8, 2026, 3:52 p.m. |
Created at: April 29, 2026, 7:56 p.m.