Triple
T9965766
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dauphin |
E195679
|
entity |
| Predicate | originOfTitle |
P87898
|
FINISHED |
| Object | lords of Dauphiné |
—
|
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: lords of Dauphiné | Statement: [Dauphin, originOfTitle, lords of Dauphiné]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originOfTitle Context triple: [Dauphin, originOfTitle, lords of Dauphiné]
-
A.
originallyTitleOf
Indicates that one title is the original title from which another work, edition, or localized title is derived.
-
B.
notableTitleOrigin
chosen
Indicates that a notable or distinguished title held by an entity originates from, or is derived from, a specified source or context.
-
C.
originalTitleOfWork
Indicates that one work is the original title under which another work was first created, published, or released.
-
D.
titleDerivedFrom
Indicates that the title of one entity is obtained or adapted from another entity.
-
E.
traditionalTitleGivenBy
Indicates that one entity has conferred or assigned a traditional or customary title to another 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_69ca82ebd1288190912f9e4482d1fa35 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb71c38488190a6f3cda11994f6a2 |
completed | April 2, 2026, 12:23 a.m. |
| PD | Predicate disambiguation | batch_69cd1d9ae19c819099fb3635e57c79be |
completed | April 1, 2026, 1:28 p.m. |
Created at: March 30, 2026, 8:47 p.m.