Triple
T30777530
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tour des Comtes de Genève |
E783716
|
entity |
| Predicate | ownerInThePast |
P128181
|
FINISHED |
| Object | Counts of Geneva |
—
|
NE NERFINISHED |
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: Counts of Geneva | Statement: [Tour des Comtes de Genève, ownerInThePast, Counts of Geneva]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ownerInThePast Context triple: [Tour des Comtes de Genève, ownerInThePast, Counts of Geneva]
-
A.
hasOwnerInThePast
chosen
Indicates that an entity was owned by another entity at some time in the past, but not necessarily in the present.
-
B.
ownerDuringMostOfHistory
Indicates that an entity has been the primary or predominant owner of another entity for the majority of the latter’s historical existence.
-
C.
ownerLater
Indicates that one entity becomes the owner of another entity at a later point in time, after some prior state or ownership.
-
D.
ownerDuringEra
Indicates that one entity is the owner of another entity specifically during a defined historical period or era.
-
E.
formerPartOwnerOf
Indicates that an entity previously held, but no longer holds, a partial ownership stake in 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_69f224b213c8819083886073f90b647e |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6db1f3ec48190a82e7d893d3c76ba |
completed | May 3, 2026, 5:20 a.m. |
| PD | Predicate disambiguation | batch_69f6d82adfa481908a5e196d2e18c73f |
completed | May 3, 2026, 5:07 a.m. |
Created at: April 29, 2026, 8:41 p.m.