Triple
T17970939
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tiye |
E449336
|
entity |
| Predicate | hadForeignCorrespondence |
P4768
|
FINISHED |
| Object | Yes |
—
|
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: Yes | Statement: [Tiye, hadForeignCorrespondence, Yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadForeignCorrespondence Context triple: [Tiye, hadForeignCorrespondence, Yes]
-
A.
correspondedWith
chosen
Indicates that two entities engaged in mutual communication, typically by exchanging messages or letters over a period of time.
-
B.
hadInternationalComponentIn
Indicates that an event, activity, or entity included a significant international element or involvement during a specified time or context.
-
C.
hadStateFrom
Indicates that an entity possessed or was in a particular state starting from a specified point in time.
-
D.
hadFort
Indicates that an entity possessed, controlled, or contained a fort at some time.
-
E.
hasCorrespondenceForm
Indicates that there exists a specific format, template, or structural representation used for the correspondence associated with an entity.
- 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_69d8b9f9927c8190a006110c8b996e61 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4b1fa67c48190936f20cea45e4599 |
completed | April 19, 2026, 10:44 a.m. |
| PD | Predicate disambiguation | batch_69e3f8fa62688190a5d5c361ab896256 |
completed | April 18, 2026, 9:34 p.m. |
Created at: April 10, 2026, 10:22 a.m.