Triple
T27329721
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karoma I Merytmut |
E689761
|
entity |
| Predicate | spouseReignContext |
P137254
|
FINISHED |
| Object | reign of Shoshenq I |
—
|
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: reign of Shoshenq I | Statement: [Karoma I Merytmut, spouseReignContext, reign of Shoshenq I]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseReignContext Context triple: [Karoma I Merytmut, spouseReignContext, reign of Shoshenq I]
-
A.
spouseReignName
Indicates the official reign name or title held by a person's spouse during their period of rule.
-
B.
spouseReignPeriod
chosen
Indicates the time span during which a person’s spouse held a position of rule or reigned.
-
C.
spouseReignOverlap
Indicates that two spouses’ periods of reign as rulers overlapped in time.
-
D.
spouseReignTerritory
Indicates that the territory specified is the domain or realm over which the spouse of the referenced person reigned or held ruling authority.
-
E.
spouseServedMonarch
Indicates that the spouse of a person held a position of service or duty to a monarch.
- 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_69ef355d4cb08190ab032c0a2e7d3753 |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69f6e6029a10819098ff21f58079e70e |
completed | May 3, 2026, 6:06 a.m. |
| PD | Predicate disambiguation | batch_69f6e3d5e8188190b1e1c2e5d1b77031 |
completed | May 3, 2026, 5:57 a.m. |
Created at: April 27, 2026, 11:37 a.m.