Triple
T25484757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Weneg-Nebty |
E638672
|
entity |
| Predicate | modernNameConventional |
P97846
|
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: [Weneg-Nebty, modernNameConventional, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: modernNameConventional Context triple: [Weneg-Nebty, modernNameConventional, yes]
-
A.
modernNameForm
chosen
Indicates that one entity is the contemporary or currently used name form corresponding to another entity’s name.
-
B.
modernNameOfficial
Indicates that an entity’s current, formally recognized name is the one specified.
-
C.
modernLocalName
Indicates the current, locally used name or designation for an entity, as recognized in the present time.
-
D.
modernNameOfArea
Indicates that one area entity represents the current or modern name of another area entity.
-
E.
hasTraditionalName
Indicates that an entity is associated with a name traditionally used or recognized for it, often rooted in long-standing cultural or historical practice.
- 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_69e75dbabeac8190bab30628f8b799d4 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f627aedf548190bc9f53c8a2d67b50 |
completed | May 2, 2026, 4:34 p.m. |
| PD | Predicate disambiguation | batch_69f623a4e1048190bbb8dd1253fdcee9 |
completed | May 2, 2026, 4:17 p.m. |
Created at: April 21, 2026, 2:32 p.m.